{
 "cells": [
  {
   "cell_type": "markdown",
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   "metadata": {
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   },
   "source": [
    "# Fine-Tune Whisper For Multilingual ASR with 🤗 Transformers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fbfa8ad5-4cdc-4512-9058-836cbbf65e1a",
   "metadata": {
    "id": "fbfa8ad5-4cdc-4512-9058-836cbbf65e1a"
   },
   "source": [
    "In this Colab, we present a step-by-step guide on how to fine-tune Whisper \n",
    "for any multilingual ASR dataset using Hugging Face 🤗 Transformers. This is a \n",
    "more \"hands-on\" version of the accompanying [blog post](https://huggingface.co/blog/fine-tune-whisper). \n",
    "For a more in-depth explanation of Whisper, the Common Voice dataset and the theory behind fine-tuning, the reader is advised to refer to the blog post."
   ]
  },
  {
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   "id": "afe0d503-ae4e-4aa7-9af4-dbcba52db41e",
   "metadata": {
    "id": "afe0d503-ae4e-4aa7-9af4-dbcba52db41e"
   },
   "source": [
    "## Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ae91ed4-9c3e-4ade-938e-f4c2dcfbfdc0",
   "metadata": {
    "id": "9ae91ed4-9c3e-4ade-938e-f4c2dcfbfdc0"
   },
   "source": [
    "Whisper is a pre-trained model for automatic speech recognition (ASR) \n",
    "published in [September 2022](https://openai.com/blog/whisper/) by the authors \n",
    "Alec Radford et al. from OpenAI. Unlike many of its predecessors, such as \n",
    "[Wav2Vec 2.0](https://arxiv.org/abs/2006.11477), which are pre-trained \n",
    "on un-labelled audio data, Whisper is pre-trained on a vast quantity of \n",
    "**labelled** audio-transcription data, 680,000 hours to be precise. \n",
    "This is an order of magnitude more data than the un-labelled audio data used \n",
    "to train Wav2Vec 2.0 (60,000 hours). What is more, 117,000 hours of this \n",
    "pre-training data is multilingual ASR data. This results in checkpoints \n",
    "that can be applied to over 96 languages, many of which are considered \n",
    "_low-resource_.\n",
    "\n",
    "When scaled to 680,000 hours of labelled pre-training data, Whisper models \n",
    "demonstrate a strong ability to generalise to many datasets and domains.\n",
    "The pre-trained checkpoints achieve competitive results to state-of-the-art \n",
    "ASR systems, with near 3% word error rate (WER) on the test-clean subset of \n",
    "LibriSpeech ASR and a new state-of-the-art on TED-LIUM with 4.7% WER (_c.f._ \n",
    "Table 8 of the [Whisper paper](https://cdn.openai.com/papers/whisper.pdf)).\n",
    "The extensive multilingual ASR knowledge acquired by Whisper during pre-training \n",
    "can be leveraged for other low-resource languages; through fine-tuning, the \n",
    "pre-trained checkpoints can be adapted for specific datasets and languages \n",
    "to further improve upon these results. We'll show just how Whisper can be fine-tuned \n",
    "for low-resource languages in this Colab."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e59b91d6-be24-4b5e-bb38-4977ea143a72",
   "metadata": {
    "id": "e59b91d6-be24-4b5e-bb38-4977ea143a72"
   },
   "source": [
    "<figure>\n",
    "<img src=\"https://raw.githubusercontent.com/sanchit-gandhi/notebooks/main/whisper_architecture.svg\" alt=\"Trulli\" style=\"width:100%\">\n",
    "<figcaption align = \"center\"><b>Figure 1:</b> Whisper model. The architecture \n",
    "follows the standard Transformer-based encoder-decoder model. A \n",
    "log-Mel spectrogram is input to the encoder. The last encoder \n",
    "hidden states are input to the decoder via cross-attention mechanisms. The \n",
    "decoder autoregressively predicts text tokens, jointly conditional on the \n",
    "encoder hidden states and previously predicted tokens. Figure source: \n",
    "<a href=\"https://openai.com/blog/whisper/\">OpenAI Whisper Blog</a>.</figcaption>\n",
    "</figure>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21b6316e-8a55-4549-a154-66d3da2ab74a",
   "metadata": {
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   },
   "source": [
    "The Whisper checkpoints come in five configurations of varying model sizes.\n",
    "The smallest four are trained on either English-only or multilingual data.\n",
    "The largest checkpoint is multilingual only. All nine of the pre-trained checkpoints \n",
    "are available on the [Hugging Face Hub](https://huggingface.co/models?search=openai/whisper). The \n",
    "checkpoints are summarised in the following table with links to the models on the Hub:\n",
    "\n",
    "| Size   | Layers | Width | Heads | Parameters | English-only                                         | Multilingual                                      |\n",
    "|--------|--------|-------|-------|------------|------------------------------------------------------|---------------------------------------------------|\n",
    "| tiny   | 4      | 384   | 6     | 39 M       | [✓](https://huggingface.co/openai/whisper-tiny.en)   | [✓](https://huggingface.co/openai/whisper-tiny.)  |\n",
    "| base   | 6      | 512   | 8     | 74 M       | [✓](https://huggingface.co/openai/whisper-base.en)   | [✓](https://huggingface.co/openai/whisper-base)   |\n",
    "| small  | 12     | 768   | 12    | 244 M      | [✓](https://huggingface.co/openai/whisper-small.en)  | [✓](https://huggingface.co/openai/whisper-small)  |\n",
    "| medium | 24     | 1024  | 16    | 769 M      | [✓](https://huggingface.co/openai/whisper-medium.en) | [✓](https://huggingface.co/openai/whisper-medium) |\n",
    "| large  | 32     | 1280  | 20    | 1550 M     | x                                                    | [✓](https://huggingface.co/openai/whisper-large)  |\n",
    "\n",
    "For demonstration purposes, we'll fine-tune the multilingual version of the \n",
    "[`\"small\"`](https://huggingface.co/openai/whisper-small) checkpoint with 244M params (~= 1GB). \n",
    "As for our data, we'll train and evaluate our system on a low-resource language \n",
    "taken from the [Common Voice](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0)\n",
    "dataset. We'll show that with as little as 8 hours of fine-tuning data, we can achieve \n",
    "strong performance in this language."
   ]
  },
  {
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   "id": "3a680dfc-cbba-4f6c-8a1f-e1a5ff3f123a",
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   },
   "source": [
    "------------------------------------------------------------------------\n",
    "\n",
    "\\\\({}^1\\\\) The name Whisper follows from the acronym “WSPSR”, which stands for “Web-scale Supervised Pre-training for Speech Recognition”."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b219c9dd-39b6-4a95-b2a1-3f547a1e7bc0",
   "metadata": {
    "id": "b219c9dd-39b6-4a95-b2a1-3f547a1e7bc0"
   },
   "source": [
    "## Load Dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "674429c5-0ab4-4adf-975b-621bb69eca38",
   "metadata": {
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   },
   "source": [
    "Using 🤗 Datasets, downloading and preparing data is extremely simple. \n",
    "We can download and prepare the Common Voice splits in just one line of code. \n",
    "\n",
    "First, ensure you have accepted the terms of use on the Hugging Face Hub: [mozilla-foundation/common_voice_11_0](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0). Once you have accepted the terms, you will have full access to the dataset and be able to download the data locally.\n",
    "\n",
    "Since Hindi is very low-resource, we'll combine the `train` and `validation` \n",
    "splits to give approximately 8 hours of training data. We'll use the 4 hours \n",
    "of `test` data as our held-out test set:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a2787582-554f-44ce-9f38-4180a5ed6b44",
   "metadata": {
    "id": "a2787582-554f-44ce-9f38-4180a5ed6b44"
   },
   "outputs": [],
   "source": [
    "# from datasets import load_dataset, DatasetDict\n",
    "\n",
    "# common_voice = DatasetDict()\n",
    "\n",
    "# common_voice[\"train\"] = load_dataset(\"mozilla-foundation/common_voice_11_0\", \"fi\", split=\"train+validation\", use_auth_token=True)\n",
    "# common_voice[\"test\"] = load_dataset(\"mozilla-foundation/common_voice_11_0\", \"fi\", split=\"test\", use_auth_token=True)\n",
    "\n",
    "# print(common_voice)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aaeb4d94-56de-4e31-8630-f7e87e1affeb",
   "metadata": {},
   "source": [
    "Load multiple datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3be04966-dfa7-4667-88cd-3c36081c9e5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset_names = [\"mozilla-foundation/common_voice_11_0\", \"facebook/voxpopuli\", \"google/fleurs\"]\n",
    "dataset_config_names = [\"fi\", \"fi\", \"fi_fi\"]\n",
    "text_column_names = [\"sentence\", \"normalized_text\", \"raw_transcription\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5e93c904-d6f6-42fa-9720-f19c58c45d8e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ubuntu/.local/lib/python3.8/site-packages/pandas/core/computation/expressions.py:20: UserWarning: Pandas requires version '2.7.3' or newer of 'numexpr' (version '2.7.1' currently installed).\n",
      "  from pandas.core.computation.check import NUMEXPR_INSTALLED\n"
     ]
    }
   ],
   "source": [
    "from datasets import Audio, interleave_datasets, IterableDataset, load_dataset\n",
    "from typing import List, Optional\n",
    "\n",
    "def load_multiple_streaming_datasets(\n",
    "    dataset_names: List,\n",
    "    dataset_config_names: List,\n",
    "    splits: Optional[List] = None,\n",
    "    text_column_names: Optional[List] = None,\n",
    "    sampling_rate: Optional[int] = 16000,\n",
    "    stopping_strategy: Optional[str] = \"all_exhausted\",\n",
    "    **kwargs\n",
    ") -> IterableDataset:\n",
    "\n",
    "    if len(dataset_names) != len(dataset_config_names):\n",
    "        raise ValueError(\n",
    "            f\"Ensure one config is passed for each dataset, got {len(dataset_names)} datasets and\"\n",
    "            f\" {len(dataset_config_names)} configs.\"\n",
    "        )\n",
    "\n",
    "    if splits is not None and len(splits) != len(dataset_names):\n",
    "        raise ValueError(\n",
    "            f\"Ensure one split is passed for each dataset, got {len(dataset_names)} datasets and {len(splits)} splits.\"\n",
    "        )\n",
    "\n",
    "    if text_column_names is not None and len(text_column_names) != len(dataset_names):\n",
    "        raise ValueError(\n",
    "            f\"Ensure one text column name is passed for each dataset, got {len(dataset_names)} datasets and\"\n",
    "            f\" {len(text_column_names)} text column names.\"\n",
    "        )\n",
    "\n",
    "    splits = splits if splits is not None else [\"train\" for i in range(len(dataset_names))]\n",
    "    text_column_names = (\n",
    "        text_column_names if text_column_names is not None else [\"text\" for i in range(len(dataset_names))]\n",
    "    )\n",
    "\n",
    "    all_datasets = []\n",
    "    # iterate over the datasets we want to interleave\n",
    "    for i, dataset_name in enumerate(dataset_names):\n",
    "        dataset = load_dataset(dataset_name, dataset_config_names[i], split=splits[i], streaming=True, **kwargs)\n",
    "        # resample to specified sampling rate\n",
    "        dataset = dataset.cast_column(\"audio\", Audio(sampling_rate))\n",
    "        #  normalise columns to [\"audio\", \"sentence\"]\n",
    "        if text_column_names[i] != \"sentence\":\n",
    "            dataset = dataset.rename_column(text_column_names[i], \"sentence\")\n",
    "        dataset = dataset.remove_columns(set(dataset.features.keys()) - set([\"audio\", \"sentence\"]))\n",
    "        all_datasets.append(dataset)\n",
    "\n",
    "    interleaved_dataset = interleave_datasets(all_datasets, stopping_strategy=stopping_strategy)\n",
    "    return interleaved_dataset\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cd0f1d04-5bad-47d5-988b-cbcd1160e645",
   "metadata": {},
   "outputs": [],
   "source": [
    "from transformers.models.whisper.english_normalizer import BasicTextNormalizer\n",
    "\n",
    "ds = load_multiple_streaming_datasets(dataset_names, dataset_config_names=dataset_config_names, text_column_names=text_column_names, use_auth_token=True)\n",
    "ds_eval = load_multiple_streaming_datasets(dataset_names, dataset_config_names=dataset_config_names, text_column_names=text_column_names, splits=['test', 'test', 'test'], use_auth_token=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5ca18d20-5c36-42de-8f15-c0bbf8754c5d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# for i, sample in enumerate(ds):\n",
    "#     print(i, sample[\"sentence\"])\n",
    "#     if i == 1:\n",
    "#         break"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d63b2d2-f68a-4d74-b7f1-5127f6d16605",
   "metadata": {
    "id": "2d63b2d2-f68a-4d74-b7f1-5127f6d16605"
   },
   "source": [
    "## Prepare Feature Extractor, Tokenizer and Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "601c3099-1026-439e-93e2-5635b3ba5a73",
   "metadata": {
    "id": "601c3099-1026-439e-93e2-5635b3ba5a73"
   },
   "source": [
    "The ASR pipeline can be de-composed into three stages: \n",
    "1) A feature extractor which pre-processes the raw audio-inputs\n",
    "2) The model which performs the sequence-to-sequence mapping \n",
    "3) A tokenizer which post-processes the model outputs to text format\n",
    "\n",
    "In 🤗 Transformers, the Whisper model has an associated feature extractor and tokenizer, \n",
    "called [WhisperFeatureExtractor](https://huggingface.co/docs/transformers/main/model_doc/whisper#transformers.WhisperFeatureExtractor)\n",
    "and [WhisperTokenizer](https://huggingface.co/docs/transformers/main/model_doc/whisper#transformers.WhisperTokenizer) \n",
    "respectively.\n",
    "\n",
    "We'll go through details for setting-up the feature extractor and tokenizer one-by-one!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "560332eb-3558-41a1-b500-e83a9f695f84",
   "metadata": {
    "id": "560332eb-3558-41a1-b500-e83a9f695f84"
   },
   "source": [
    "### Load WhisperFeatureExtractor"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32ec8068-0bd7-412d-b662-0edb9d1e7365",
   "metadata": {
    "id": "32ec8068-0bd7-412d-b662-0edb9d1e7365"
   },
   "source": [
    "The Whisper feature extractor performs two operations:\n",
    "1. Pads / truncates the audio inputs to 30s: any audio inputs shorter than 30s are padded to 30s with silence (zeros), and those longer that 30s are truncated to 30s\n",
    "2. Converts the audio inputs to _log-Mel spectrogram_ input features, a visual representation of the audio and the form of the input expected by the Whisper model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "589d9ec1-d12b-4b64-93f7-04c63997da19",
   "metadata": {
    "id": "589d9ec1-d12b-4b64-93f7-04c63997da19"
   },
   "source": [
    "<figure>\n",
    "<img src=\"https://raw.githubusercontent.com/sanchit-gandhi/notebooks/main/spectrogram.jpg\" alt=\"Trulli\" style=\"width:100%\">\n",
    "<figcaption align = \"center\"><b>Figure 2:</b> Conversion of sampled audio array to log-Mel spectrogram.\n",
    "Left: sampled 1-dimensional audio signal. Right: corresponding log-Mel spectrogram. Figure source:\n",
    "<a href=\"https://ai.googleblog.com/2019/04/specaugment-new-data-augmentation.html\">Google SpecAugment Blog</a>.\n",
    "</figcaption>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2ef54d5-b946-4c1d-9fdc-adc5d01b46aa",
   "metadata": {
    "id": "b2ef54d5-b946-4c1d-9fdc-adc5d01b46aa"
   },
   "source": [
    "We'll load the feature extractor from the pre-trained checkpoint with the default values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "bc77d7bb-f9e2-47f5-b663-30f7a4321ce5",
   "metadata": {
    "id": "bc77d7bb-f9e2-47f5-b663-30f7a4321ce5"
   },
   "outputs": [],
   "source": [
    "from transformers import WhisperFeatureExtractor\n",
    "\n",
    "feature_extractor = WhisperFeatureExtractor.from_pretrained(\"openai/whisper-large\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93748af7-b917-4ecf-a0c8-7d89077ff9cb",
   "metadata": {
    "id": "93748af7-b917-4ecf-a0c8-7d89077ff9cb"
   },
   "source": [
    "### Load WhisperTokenizer"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2bc82609-a9fb-447a-a2af-99597c864029",
   "metadata": {
    "id": "2bc82609-a9fb-447a-a2af-99597c864029"
   },
   "source": [
    "The Whisper model outputs a sequence of _token ids_. The tokenizer maps each of these token ids to their corresponding text string. For Hindi, we can load the pre-trained tokenizer and use it for fine-tuning without any further modifications. We simply have to \n",
    "specify the target language and the task. These arguments inform the \n",
    "tokenizer to prefix the language and task tokens to the start of encoded \n",
    "label sequences:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c7b07f9b-ae0e-4f89-98f0-0c50d432eab6",
   "metadata": {
    "id": "c7b07f9b-ae0e-4f89-98f0-0c50d432eab6",
    "outputId": "5c004b44-86e7-4e00-88be-39e0af5eed69"
   },
   "outputs": [],
   "source": [
    "from transformers import WhisperTokenizer\n",
    "\n",
    "tokenizer = WhisperTokenizer.from_pretrained(\"openai/whisper-large\", language=\"Finnish\", task=\"transcribe\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2ef23f3-f4a8-483a-a2dc-080a7496cb1b",
   "metadata": {
    "id": "d2ef23f3-f4a8-483a-a2dc-080a7496cb1b"
   },
   "source": [
    "### Combine To Create A WhisperProcessor"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ff67654-5a29-4bb8-a69d-0228946c6f8d",
   "metadata": {
    "id": "5ff67654-5a29-4bb8-a69d-0228946c6f8d"
   },
   "source": [
    "To simplify using the feature extractor and tokenizer, we can _wrap_ \n",
    "both into a single `WhisperProcessor` class. This processor object \n",
    "inherits from the `WhisperFeatureExtractor` and `WhisperProcessor`, \n",
    "and can be used on the audio inputs and model predictions as required. \n",
    "In doing so, we only need to keep track of two objects during training: \n",
    "the `processor` and the `model`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "77d9f0c5-8607-4642-a8ac-c3ab2e223ea6",
   "metadata": {
    "id": "77d9f0c5-8607-4642-a8ac-c3ab2e223ea6"
   },
   "outputs": [],
   "source": [
    "from transformers import WhisperProcessor\n",
    "\n",
    "processor = WhisperProcessor.from_pretrained(\"openai/whisper-large\", language=\"Finnish\", task=\"transcribe\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "381acd09-0b0f-4d04-9eb3-f028ac0e5f2c",
   "metadata": {
    "id": "381acd09-0b0f-4d04-9eb3-f028ac0e5f2c"
   },
   "source": [
    "### Prepare Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89e12c2e-2f14-479b-987b-f0c75c881095",
   "metadata": {},
   "source": [
    "Now we can write a function to prepare our data ready for the model:\n",
    "1. We load and resample the audio data by calling `batch[\"audio\"]`. As explained above, 🤗 Datasets performs any necessary resampling operations on the fly.\n",
    "2. We use the feature extractor to compute the log-Mel spectrogram input features from our 1-dimensional audio array.\n",
    "3. We perform any optional pre-processing (lower-case or remove punctuation).\n",
    "4. We encode the transcriptions to label ids through the use of the tokenizer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c085911c-a10a-41ef-8874-306e0503e9bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "def preprocess_data(batch, normalizer, lower=False, punctuation=False):\n",
    "    audio = batch[\"audio\"]\n",
    "    # compute log-Mel input features from input audio array \n",
    "    batch[\"input_features\"] = processor.feature_extractor(audio[\"array\"], sampling_rate=audio[\"sampling_rate\"]).input_features[0]\n",
    "    # compute input length of audio sample in seconds\n",
    "    batch[\"input_length\"] = len(audio[\"array\"]) / audio[\"sampling_rate\"]\n",
    "        \n",
    "    # optional pre-processing steps\n",
    "    transcription = batch[\"sentence\"]\n",
    "    if lower:\n",
    "        transcription = transcription.lower()\n",
    "    if punctuation:\n",
    "        transcription = normalizer(transcription).strip()\n",
    "    \n",
    "    # encode target text to label ids\n",
    "    batch[\"labels\"] = processor.tokenizer(transcription).input_ids\n",
    "    \n",
    "    return batch"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c960965-9fb6-466f-9dbd-c9d43e71d9d0",
   "metadata": {
    "id": "70b319fb-2439-4ef6-a70d-a47bf41c4a13"
   },
   "source": [
    "We can apply the data preparation function to all of our training examples using dataset's `.map` method. The argument `num_proc` specifies how many CPU cores to use. Setting `num_proc` > 1 will enable multiprocessing. If the `.map` method hangs with multiprocessing, set `num_proc=1` and process the dataset sequentially."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7b73ab39-ffaf-4b9e-86e5-782963c6134b",
   "metadata": {
    "id": "7b73ab39-ffaf-4b9e-86e5-782963c6134b"
   },
   "outputs": [],
   "source": [
    "normalizer = BasicTextNormalizer()\n",
    "\n",
    "ds = ds.map(lambda x: preprocess_data(x, normalizer, lower=True, punctuation=False))\n",
    "ds_eval = ds_eval.map(lambda x: preprocess_data(x, normalizer, lower=True, punctuation=False))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54ce0fdb-7218-4a4d-b175-383980fec0df",
   "metadata": {},
   "source": [
    "Finally, we filter any training data with audio samples longer than 30s. These samples would otherwise be truncated by the Whisper feature-extractor which could affect the stability of training. We define a function that returns `True` for samples that are less than 30s, and `False` for those that are longer:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "01cb25ef-4bb0-4325-9461-f59198acadf6",
   "metadata": {},
   "outputs": [],
   "source": [
    "max_input_length = 30.0\n",
    "\n",
    "def is_audio_in_length_range(length):\n",
    "    return length < max_input_length"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30e676a8-7ca8-4850-8c5d-5b2b00d13fba",
   "metadata": {},
   "source": [
    "We apply our filter function to all samples of our training dataset through 🤗 Datasets' `.filter` method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "333f7f6e-6053-4d3b-8924-c733c79b82ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = ds.filter(\n",
    "    is_audio_in_length_range,\n",
    "    input_columns=[\"input_length\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "263a5a58-0239-4a25-b0df-c625fc9c5810",
   "metadata": {
    "id": "263a5a58-0239-4a25-b0df-c625fc9c5810"
   },
   "source": [
    "## Training and Evaluation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a693e768-c5a6-453f-89a1-b601dcf7daf7",
   "metadata": {
    "id": "a693e768-c5a6-453f-89a1-b601dcf7daf7"
   },
   "source": [
    "Now that we've prepared our data, we're ready to dive into the training pipeline. \n",
    "The [🤗 Trainer](https://huggingface.co/transformers/master/main_classes/trainer.html?highlight=trainer)\n",
    "will do much of the heavy lifting for us. All we have to do is:\n",
    "\n",
    "- Define a data collator: the data collator takes our pre-processed data and prepares PyTorch tensors ready for the model.\n",
    "\n",
    "- Evaluation metrics: during evaluation, we want to evaluate the model using the [word error rate (WER)](https://huggingface.co/metrics/wer) metric. We need to define a `compute_metrics` function that handles this computation.\n",
    "\n",
    "- Load a pre-trained checkpoint: we need to load a pre-trained checkpoint and configure it correctly for training.\n",
    "\n",
    "- Define the training configuration: this will be used by the 🤗 Trainer to define the training schedule.\n",
    "\n",
    "Once we've fine-tuned the model, we will evaluate it on the test data to verify that we have correctly trained it \n",
    "to transcribe speech in Hindi."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d230e6d-624c-400a-bbf5-fa660881df25",
   "metadata": {
    "id": "8d230e6d-624c-400a-bbf5-fa660881df25"
   },
   "source": [
    "### Define a Data Collator"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04def221-0637-4a69-b242-d3f0c1d0ee78",
   "metadata": {
    "id": "04def221-0637-4a69-b242-d3f0c1d0ee78"
   },
   "source": [
    "The data collator for a sequence-to-sequence speech model is unique in the sense that it \n",
    "treats the `input_features` and `labels` independently: the  `input_features` must be \n",
    "handled by the feature extractor and the `labels` by the tokenizer.\n",
    "\n",
    "The `input_features` are already padded to 30s and converted to a log-Mel spectrogram \n",
    "of fixed dimension by action of the feature extractor, so all we have to do is convert the `input_features`\n",
    "to batched PyTorch tensors. We do this using the feature extractor's `.pad` method with `return_tensors=pt`.\n",
    "\n",
    "The `labels` on the other hand are un-padded. We first pad the sequences\n",
    "to the maximum length in the batch using the tokenizer's `.pad` method. The padding tokens \n",
    "are then replaced by `-100` so that these tokens are **not** taken into account when \n",
    "computing the loss. We then cut the BOS token from the start of the label sequence as we \n",
    "append it later during training.\n",
    "\n",
    "We can leverage the `WhisperProcessor` we defined earlier to perform both the \n",
    "feature extractor and the tokenizer operations:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "8326221e-ec13-4731-bb4e-51e5fc1486c5",
   "metadata": {
    "id": "8326221e-ec13-4731-bb4e-51e5fc1486c5"
   },
   "outputs": [],
   "source": [
    "import torch\n",
    "\n",
    "from dataclasses import dataclass\n",
    "from typing import Any, Dict, List, Union\n",
    "\n",
    "@dataclass\n",
    "class DataCollatorSpeechSeq2SeqWithPadding:\n",
    "    processor: Any\n",
    "\n",
    "    def __call__(self, features: List[Dict[str, Union[List[int], torch.Tensor]]]) -> Dict[str, torch.Tensor]:\n",
    "        # split inputs and labels since they have to be of different lengths and need different padding methods\n",
    "        # first treat the audio inputs by simply returning torch tensors\n",
    "\n",
    "        input_features = [{\"input_features\": feature[\"input_features\"]} for feature in features]\n",
    "        batch = self.processor.feature_extractor.pad(input_features, return_tensors=\"pt\")\n",
    "\n",
    "        # get the tokenized label sequences\n",
    "        label_features = [{\"input_ids\": feature[\"labels\"]} for feature in features]\n",
    "        # pad the labels to max length\n",
    "        labels_batch = self.processor.tokenizer.pad(label_features, return_tensors=\"pt\")\n",
    "\n",
    "        # replace padding with -100 to ignore loss correctly\n",
    "        labels = labels_batch[\"input_ids\"].masked_fill(labels_batch.attention_mask.ne(1), -100)\n",
    "\n",
    "        # if bos token is appended in previous tokenization step,\n",
    "        # cut bos token here as it's append later anyways\n",
    "        if (labels[:, 0] == self.processor.tokenizer.bos_token_id).all().cpu().item():\n",
    "            labels = labels[:, 1:]\n",
    "\n",
    "        batch[\"labels\"] = labels\n",
    "\n",
    "        return batch"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3cae7dbf-8a50-456e-a3a8-7fd005390f86",
   "metadata": {
    "id": "3cae7dbf-8a50-456e-a3a8-7fd005390f86"
   },
   "source": [
    "Let's initialise the data collator we've just defined:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "fc834702-c0d3-4a96-b101-7b87be32bf42",
   "metadata": {
    "id": "fc834702-c0d3-4a96-b101-7b87be32bf42"
   },
   "outputs": [],
   "source": [
    "data_collator = DataCollatorSpeechSeq2SeqWithPadding(processor=processor)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d62bb2ab-750a-45e7-82e9-61d6f4805698",
   "metadata": {
    "id": "d62bb2ab-750a-45e7-82e9-61d6f4805698"
   },
   "source": [
    "### Evaluation Metrics"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66fee1a7-a44c-461e-b047-c3917221572e",
   "metadata": {
    "id": "66fee1a7-a44c-461e-b047-c3917221572e"
   },
   "source": [
    "We'll use the word error rate (WER) metric, the 'de-facto' metric for assessing \n",
    "ASR systems. For more information, refer to the WER [docs](https://huggingface.co/metrics/wer). We'll load the WER metric from 🤗 Evaluate:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b22b4011-f31f-4b57-b684-c52332f92890",
   "metadata": {
    "id": "b22b4011-f31f-4b57-b684-c52332f92890"
   },
   "outputs": [],
   "source": [
    "import evaluate\n",
    "\n",
    "metric = evaluate.load(\"wer\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f32cab6-31f0-4cb9-af4c-40ba0f5fc508",
   "metadata": {
    "id": "4f32cab6-31f0-4cb9-af4c-40ba0f5fc508"
   },
   "source": [
    "We then simply have to define a function that takes our model \n",
    "predictions and returns the WER metric. This function, called\n",
    "`compute_metrics`, first replaces `-100` with the `pad_token_id`\n",
    "in the `label_ids` (undoing the step we applied in the \n",
    "data collator to ignore padded tokens correctly in the loss).\n",
    "It then decodes the predicted and label ids to strings. Finally,\n",
    "it computes the WER between the predictions and reference labels. \n",
    "Here, we have the option of evaluating with the 'normalised' transcriptions \n",
    "and predictions. We recommend you set this to `True` to benefit from the WER \n",
    "improvement obtained by normalising the transcriptions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "23959a70-22d0-4ffe-9fa1-72b61e75bb52",
   "metadata": {
    "id": "23959a70-22d0-4ffe-9fa1-72b61e75bb52"
   },
   "outputs": [],
   "source": [
    "# evaluate with the 'normalised' WER\n",
    "do_normalize_eval = True\n",
    "\n",
    "def compute_metrics(pred):\n",
    "    pred_ids = pred.predictions\n",
    "    label_ids = pred.label_ids\n",
    "\n",
    "    # replace -100 with the pad_token_id\n",
    "    label_ids[label_ids == -100] = processor.tokenizer.pad_token_id\n",
    "\n",
    "    # we do not want to group tokens when computing the metrics\n",
    "    pred_str = processor.tokenizer.batch_decode(pred_ids, skip_special_tokens=True)\n",
    "    label_str = processor.tokenizer.batch_decode(label_ids, skip_special_tokens=True)\n",
    "\n",
    "    if do_normalize_eval:\n",
    "        pred_str = [normalizer(pred) for pred in pred_str]\n",
    "        label_str = [normalizer(label) for label in label_str]\n",
    "\n",
    "    wer = 100 * metric.compute(predictions=pred_str, references=label_str)\n",
    "\n",
    "    return {\"wer\": wer}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "daf2a825-6d9f-4a23-b145-c37c0039075b",
   "metadata": {
    "id": "daf2a825-6d9f-4a23-b145-c37c0039075b"
   },
   "source": [
    "### Load a Pre-Trained Checkpoint"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "437a97fa-4864-476b-8abc-f28b8166cfa5",
   "metadata": {
    "id": "437a97fa-4864-476b-8abc-f28b8166cfa5"
   },
   "source": [
    "Now let's load the pre-trained Whisper `small` checkpoint. Again, this \n",
    "is trivial through use of 🤗 Transformers!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5a10cc4b-07ec-4ebd-ac1d-7c601023594f",
   "metadata": {
    "id": "5a10cc4b-07ec-4ebd-ac1d-7c601023594f"
   },
   "outputs": [],
   "source": [
    "from transformers import WhisperForConditionalGeneration\n",
    "\n",
    "model = WhisperForConditionalGeneration.from_pretrained(\"openai/whisper-large\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a15ead5f-2277-4a39-937b-585c2497b2df",
   "metadata": {
    "id": "a15ead5f-2277-4a39-937b-585c2497b2df"
   },
   "source": [
    "Override generation arguments - no tokens are forced as decoder outputs (see [`forced_decoder_ids`](https://huggingface.co/docs/transformers/main_classes/text_generation#transformers.generation_utils.GenerationMixin.generate.forced_decoder_ids)), no tokens are suppressed during generation (see [`suppress_tokens`](https://huggingface.co/docs/transformers/main_classes/text_generation#transformers.generation_utils.GenerationMixin.generate.suppress_tokens)). Set `use_cache` to False since we're using gradient checkpointing, and the two are incompatible:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "62038ba3-88ed-4fce-84db-338f50dcd04f",
   "metadata": {
    "id": "62038ba3-88ed-4fce-84db-338f50dcd04f"
   },
   "outputs": [],
   "source": [
    "model.config.forced_decoder_ids = None\n",
    "model.config.suppress_tokens = []\n",
    "model.config.use_cache = False"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2178dea4-80ca-47b6-b6ea-ba1915c90c06",
   "metadata": {
    "id": "2178dea4-80ca-47b6-b6ea-ba1915c90c06"
   },
   "source": [
    "### Define the Training Configuration"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c21af1e9-0188-4134-ac82-defc7bdcc436",
   "metadata": {
    "id": "c21af1e9-0188-4134-ac82-defc7bdcc436"
   },
   "source": [
    "In the final step, we define all the parameters related to training. For more detail on the training arguments, refer to the Seq2SeqTrainingArguments [docs](https://huggingface.co/docs/transformers/main_classes/trainer#transformers.Seq2SeqTrainingArguments)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "0ae3e9af-97b7-4aa0-ae85-20b23b5bcb3a",
   "metadata": {
    "id": "0ae3e9af-97b7-4aa0-ae85-20b23b5bcb3a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2022-12-16 13:29:15,889] [INFO] [comm.py:654:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl\n"
     ]
    }
   ],
   "source": [
    "from transformers import Seq2SeqTrainingArguments\n",
    "import os\n",
    "\n",
    "# ENABLE DEEPSPEED\n",
    "os.environ[\"MASTER_ADDR\"] = \"localhost\"\n",
    "os.environ[\"MASTER_PORT\"] = \"9994\"  # modify if RuntimeError: Address already in use\n",
    "os.environ[\"RANK\"] = \"0\"\n",
    "os.environ[\"LOCAL_RANK\"] = \"0\"\n",
    "os.environ[\"WORLD_SIZE\"] = \"1\"\n",
    "\n",
    "training_args = Seq2SeqTrainingArguments(\n",
    "    deepspeed=\"ds_config.json\",\n",
    "    output_dir=\"./\",\n",
    "    per_device_train_batch_size=32,\n",
    "    gradient_accumulation_steps=2,  # increase by 2x for every 2x decrease in batch size\n",
    "    learning_rate=1e-5,\n",
    "    warmup_steps=100,\n",
    "    max_steps=1000,\n",
    "    gradient_checkpointing=True,\n",
    "    fp16=True,\n",
    "    evaluation_strategy=\"steps\",\n",
    "    per_device_eval_batch_size=8,\n",
    "    predict_with_generate=True,\n",
    "    generation_max_length=225,\n",
    "    save_steps=100,\n",
    "    eval_steps=100,\n",
    "    logging_steps=25,\n",
    "    report_to=[\"tensorboard\"],\n",
    "    load_best_model_at_end=True,\n",
    "    metric_for_best_model=\"wer\",\n",
    "    greater_is_better=False,\n",
    "    push_to_hub=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3a944d8-3112-4552-82a0-be25988b3857",
   "metadata": {
    "id": "b3a944d8-3112-4552-82a0-be25988b3857"
   },
   "source": [
    "**Note**: if one does not want to upload the model checkpoints to the Hub, \n",
    "set `push_to_hub=False`."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bac29114-d226-4f54-97cf-8718c9f94e1e",
   "metadata": {
    "id": "bac29114-d226-4f54-97cf-8718c9f94e1e"
   },
   "source": [
    "We can forward the training arguments to the 🤗 Trainer along with our model,\n",
    "dataset, data collator and `compute_metrics` function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d546d7fe-0543-479a-b708-2ebabec19493",
   "metadata": {
    "id": "d546d7fe-0543-479a-b708-2ebabec19493"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ubuntu/whisper-large-fi/./ is already a clone of https://huggingface.co/TeemuSo/whisper-large-fi. Make sure you pull the latest changes with `repo.git_pull()`.\n",
      "max_steps is given, it will override any value given in num_train_epochs\n",
      "Using cuda_amp half precision backend\n"
     ]
    }
   ],
   "source": [
    "from transformers import Seq2SeqTrainer\n",
    "\n",
    "trainer = Seq2SeqTrainer(\n",
    "    args=training_args,\n",
    "    model=model,\n",
    "    train_dataset=ds,\n",
    "    eval_dataset=ds_eval,\n",
    "    data_collator=data_collator,\n",
    "    compute_metrics=compute_metrics,\n",
    "    tokenizer=processor.feature_extractor,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "uOrRhDGtN5S4",
   "metadata": {
    "id": "uOrRhDGtN5S4"
   },
   "source": [
    "We'll save the processor object once before starting training. Since the processor is not trainable, it won't change over the course of training:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "-2zQwMfEOBJq",
   "metadata": {
    "id": "-2zQwMfEOBJq"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Feature extractor saved in ./preprocessor_config.json\n",
      "tokenizer config file saved in ./tokenizer_config.json\n",
      "Special tokens file saved in ./special_tokens_map.json\n",
      "added tokens file saved in ./added_tokens.json\n"
     ]
    }
   ],
   "source": [
    "processor.save_pretrained(training_args.output_dir)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f404cf9-4345-468c-8196-4bd101d9bd51",
   "metadata": {
    "id": "7f404cf9-4345-468c-8196-4bd101d9bd51"
   },
   "source": [
    "### Training"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e8b8d56-5a70-4f68-bd2e-f0752d0bd112",
   "metadata": {
    "id": "5e8b8d56-5a70-4f68-bd2e-f0752d0bd112"
   },
   "source": [
    "Training will take approximately 5-10 hours depending on your GPU. The peak GPU memory for the given training configuration is approximately 36GB. \n",
    "Depending on your GPU, it is possible that you will encounter a CUDA `\"out-of-memory\"` error when you launch training. \n",
    "In this case, you can reduce the `per_device_train_batch_size` incrementally by factors of 2 \n",
    "and employ [`gradient_accumulation_steps`](https://huggingface.co/docs/transformers/main_classes/trainer#transformers.Seq2SeqTrainingArguments.gradient_accumulation_steps)\n",
    "to compensate.\n",
    "\n",
    "To launch training, simply execute:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ee8b7b8e-1c9a-4d77-9137-1778a629e6de",
   "metadata": {
    "id": "ee8b7b8e-1c9a-4d77-9137-1778a629e6de"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2022-12-16 13:29:20,270] [INFO] [logging.py:68:log_dist] [Rank 0] DeepSpeed info: version=0.7.7, git-hash=unknown, git-branch=unknown\n",
      "[2022-12-16 13:29:21,099] [INFO] [logging.py:68:log_dist] [Rank 0] DeepSpeed Flops Profiler Enabled: False\n",
      "[2022-12-16 13:29:22,285] [WARNING] [cpu_adam.py:83:__init__] FP16 params for CPUAdam may not work on AMD CPUs\n",
      "Installed CUDA version 11.6 does not match the version torch was compiled with 11.7 but since the APIs are compatible, accepting this combination\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using /home/ubuntu/.cache/torch_extensions/py38_cu117 as PyTorch extensions root...\n",
      "Detected CUDA files, patching ldflags\n",
      "Emitting ninja build file /home/ubuntu/.cache/torch_extensions/py38_cu117/cpu_adam/build.ninja...\n",
      "Building extension module cpu_adam...\n",
      "Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)\n",
      "Loading extension module cpu_adam...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Time to load cpu_adam op: 2.935727119445801 seconds\n",
      "[2022-12-16 13:29:27,577] [INFO] [logging.py:68:log_dist] [Rank 0] Using DeepSpeed Optimizer param name adamw as basic optimizer\n",
      "[2022-12-16 13:29:27,898] [INFO] [logging.py:68:log_dist] [Rank 0] DeepSpeed Basic Optimizer = DeepSpeedCPUAdam\n",
      "[2022-12-16 13:29:27,899] [INFO] [utils.py:52:is_zero_supported_optimizer] Checking ZeRO support for optimizer=DeepSpeedCPUAdam type=<class 'deepspeed.ops.adam.cpu_adam.DeepSpeedCPUAdam'>\n",
      "[2022-12-16 13:29:27,899] [INFO] [logging.py:68:log_dist] [Rank 0] Creating fp16 ZeRO stage 2 optimizer\n",
      "[2022-12-16 13:29:27,900] [INFO] [stage_1_and_2.py:140:__init__] Reduce bucket size 200000000\n",
      "[2022-12-16 13:29:27,901] [INFO] [stage_1_and_2.py:141:__init__] Allgather bucket size 200000000\n",
      "[2022-12-16 13:29:27,901] [INFO] [stage_1_and_2.py:142:__init__] CPU Offload: True\n",
      "[2022-12-16 13:29:27,901] [INFO] [stage_1_and_2.py:143:__init__] Round robin gradient partitioning: False\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using /home/ubuntu/.cache/torch_extensions/py38_cu117 as PyTorch extensions root...\n",
      "Emitting ninja build file /home/ubuntu/.cache/torch_extensions/py38_cu117/utils/build.ninja...\n",
      "Building extension module utils...\n",
      "Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)\n",
      "Loading extension module utils...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Time to load utils op: 0.45751523971557617 seconds\n",
      "Rank: 0 partition count [1] and sizes[(1543304960, False)] \n",
      "[2022-12-16 13:29:31,546] [INFO] [utils.py:827:see_memory_usage] Before initializing optimizer states\n",
      "[2022-12-16 13:29:31,548] [INFO] [utils.py:828:see_memory_usage] MA 3.0 GB         Max_MA 3.0 GB         CA 5.99 GB         Max_CA 6 GB \n",
      "[2022-12-16 13:29:31,549] [INFO] [utils.py:836:see_memory_usage] CPU Virtual Memory:  used = 15.24 GB, percent = 7.8%\n",
      "[2022-12-16 13:29:35,444] [INFO] [utils.py:827:see_memory_usage] After initializing optimizer states\n",
      "[2022-12-16 13:29:35,445] [INFO] [utils.py:828:see_memory_usage] MA 3.0 GB         Max_MA 3.0 GB         CA 5.99 GB         Max_CA 6 GB \n",
      "[2022-12-16 13:29:35,446] [INFO] [utils.py:836:see_memory_usage] CPU Virtual Memory:  used = 34.89 GB, percent = 17.7%\n",
      "[2022-12-16 13:29:35,447] [INFO] [stage_1_and_2.py:525:__init__] optimizer state initialized\n",
      "[2022-12-16 13:29:35,575] [INFO] [utils.py:827:see_memory_usage] After initializing ZeRO optimizer\n",
      "[2022-12-16 13:29:35,576] [INFO] [utils.py:828:see_memory_usage] MA 3.0 GB         Max_MA 3.0 GB         CA 5.99 GB         Max_CA 6 GB \n",
      "[2022-12-16 13:29:35,577] [INFO] [utils.py:836:see_memory_usage] CPU Virtual Memory:  used = 34.89 GB, percent = 17.7%\n",
      "[2022-12-16 13:29:35,602] [INFO] [logging.py:68:log_dist] [Rank 0] DeepSpeed Final Optimizer = adamw\n",
      "[2022-12-16 13:29:35,602] [INFO] [logging.py:68:log_dist] [Rank 0] DeepSpeed using configured LR scheduler = WarmupLR\n",
      "[2022-12-16 13:29:35,603] [INFO] [logging.py:68:log_dist] [Rank 0] DeepSpeed LR Scheduler = <deepspeed.runtime.lr_schedules.WarmupLR object at 0x7fa7b19420d0>\n",
      "[2022-12-16 13:29:35,604] [INFO] [logging.py:68:log_dist] [Rank 0] step=0, skipped=0, lr=[1e-05], mom=[[0.9, 0.999]]\n",
      "[2022-12-16 13:29:35,606] [INFO] [config.py:1020:print] DeepSpeedEngine configuration:\n",
      "[2022-12-16 13:29:35,607] [INFO] [config.py:1024:print]   activation_checkpointing_config  {\n",
      "    \"partition_activations\": false, \n",
      "    \"contiguous_memory_optimization\": false, \n",
      "    \"cpu_checkpointing\": false, \n",
      "    \"number_checkpoints\": null, \n",
      "    \"synchronize_checkpoint_boundary\": false, \n",
      "    \"profile\": false\n",
      "}\n",
      "[2022-12-16 13:29:35,607] [INFO] [config.py:1024:print]   aio_config ................... {'block_size': 1048576, 'queue_depth': 8, 'thread_count': 1, 'single_submit': False, 'overlap_events': True}\n",
      "[2022-12-16 13:29:35,608] [INFO] [config.py:1024:print]   amp_enabled .................. False\n",
      "[2022-12-16 13:29:35,608] [INFO] [config.py:1024:print]   amp_params ................... False\n",
      "[2022-12-16 13:29:35,609] [INFO] [config.py:1024:print]   autotuning_config ............ {\n",
      "    \"enabled\": false, \n",
      "    \"start_step\": null, \n",
      "    \"end_step\": null, \n",
      "    \"metric_path\": null, \n",
      "    \"arg_mappings\": null, \n",
      "    \"metric\": \"throughput\", \n",
      "    \"model_info\": null, \n",
      "    \"results_dir\": \"autotuning_results\", \n",
      "    \"exps_dir\": \"autotuning_exps\", \n",
      "    \"overwrite\": true, \n",
      "    \"fast\": true, \n",
      "    \"start_profile_step\": 3, \n",
      "    \"end_profile_step\": 5, \n",
      "    \"tuner_type\": \"gridsearch\", \n",
      "    \"tuner_early_stopping\": 5, \n",
      "    \"tuner_num_trials\": 50, \n",
      "    \"model_info_path\": null, \n",
      "    \"mp_size\": 1, \n",
      "    \"max_train_batch_size\": null, \n",
      "    \"min_train_batch_size\": 1, \n",
      "    \"max_train_micro_batch_size_per_gpu\": 1.024000e+03, \n",
      "    \"min_train_micro_batch_size_per_gpu\": 1, \n",
      "    \"num_tuning_micro_batch_sizes\": 3\n",
      "}\n",
      "[2022-12-16 13:29:35,609] [INFO] [config.py:1024:print]   bfloat16_enabled ............. False\n",
      "[2022-12-16 13:29:35,611] [INFO] [config.py:1024:print]   checkpoint_parallel_write_pipeline  False\n",
      "[2022-12-16 13:29:35,611] [INFO] [config.py:1024:print]   checkpoint_tag_validation_enabled  True\n",
      "[2022-12-16 13:29:35,611] [INFO] [config.py:1024:print]   checkpoint_tag_validation_fail  False\n",
      "[2022-12-16 13:29:35,612] [INFO] [config.py:1024:print]   comms_config ................. <deepspeed.comm.config.DeepSpeedCommsConfig object at 0x7fa7b19429a0>\n",
      "[2022-12-16 13:29:35,612] [INFO] [config.py:1024:print]   communication_data_type ...... None\n",
      "[2022-12-16 13:29:35,613] [INFO] [config.py:1024:print]   compression_config ........... {'weight_quantization': {'shared_parameters': {'enabled': False, 'quantizer_kernel': False, 'schedule_offset': 0, 'quantize_groups': 1, 'quantize_verbose': False, 'quantization_type': 'symmetric', 'quantize_weight_in_forward': False, 'rounding': 'nearest', 'fp16_mixed_quantize': False, 'quantize_change_ratio': 0.001}, 'different_groups': {}}, 'activation_quantization': {'shared_parameters': {'enabled': False, 'quantization_type': 'symmetric', 'range_calibration': 'dynamic', 'schedule_offset': 1000}, 'different_groups': {}}, 'sparse_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'row_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'head_pruning': {'shared_parameters': {'enabled': False, 'method': 'topk', 'schedule_offset': 1000}, 'different_groups': {}}, 'channel_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'layer_reduction': {'enabled': False}}\n",
      "[2022-12-16 13:29:35,613] [INFO] [config.py:1024:print]   curriculum_enabled ........... False\n",
      "[2022-12-16 13:29:35,613] [INFO] [config.py:1024:print]   curriculum_params ............ False\n",
      "[2022-12-16 13:29:35,614] [INFO] [config.py:1024:print]   dataloader_drop_last ......... False\n",
      "[2022-12-16 13:29:35,614] [INFO] [config.py:1024:print]   disable_allgather ............ False\n",
      "[2022-12-16 13:29:35,614] [INFO] [config.py:1024:print]   dump_state ................... False\n",
      "[2022-12-16 13:29:35,615] [INFO] [config.py:1024:print]   dynamic_loss_scale_args ...... {'init_scale': 65536, 'scale_window': 1000, 'delayed_shift': 2, 'min_scale': 1}\n",
      "[2022-12-16 13:29:35,615] [INFO] [config.py:1024:print]   eigenvalue_enabled ........... False\n",
      "[2022-12-16 13:29:35,616] [INFO] [config.py:1024:print]   eigenvalue_gas_boundary_resolution  1\n",
      "[2022-12-16 13:29:35,616] [INFO] [config.py:1024:print]   eigenvalue_layer_name ........ bert.encoder.layer\n",
      "[2022-12-16 13:29:35,616] [INFO] [config.py:1024:print]   eigenvalue_layer_num ......... 0\n",
      "[2022-12-16 13:29:35,619] [INFO] [config.py:1024:print]   eigenvalue_max_iter .......... 100\n",
      "[2022-12-16 13:29:35,619] [INFO] [config.py:1024:print]   eigenvalue_stability ......... 1e-06\n",
      "[2022-12-16 13:29:35,619] [INFO] [config.py:1024:print]   eigenvalue_tol ............... 0.01\n",
      "[2022-12-16 13:29:35,620] [INFO] [config.py:1024:print]   eigenvalue_verbose ........... False\n",
      "[2022-12-16 13:29:35,621] [INFO] [config.py:1024:print]   elasticity_enabled ........... False\n",
      "[2022-12-16 13:29:35,621] [INFO] [config.py:1024:print]   flops_profiler_config ........ {\n",
      "    \"enabled\": false, \n",
      "    \"profile_step\": 1, \n",
      "    \"module_depth\": -1, \n",
      "    \"top_modules\": 1, \n",
      "    \"detailed\": true, \n",
      "    \"output_file\": null\n",
      "}\n",
      "[2022-12-16 13:29:35,622] [INFO] [config.py:1024:print]   fp16_auto_cast ............... False\n",
      "[2022-12-16 13:29:35,622] [INFO] [config.py:1024:print]   fp16_enabled ................. True\n",
      "[2022-12-16 13:29:35,622] [INFO] [config.py:1024:print]   fp16_master_weights_and_gradients  False\n",
      "[2022-12-16 13:29:35,623] [INFO] [config.py:1024:print]   global_rank .................. 0\n",
      "[2022-12-16 13:29:35,623] [INFO] [config.py:1024:print]   grad_accum_dtype ............. None\n",
      "[2022-12-16 13:29:35,623] [INFO] [config.py:1024:print]   gradient_accumulation_steps .. 2\n",
      "[2022-12-16 13:29:35,624] [INFO] [config.py:1024:print]   gradient_clipping ............ 1.0\n",
      "[2022-12-16 13:29:35,624] [INFO] [config.py:1024:print]   gradient_predivide_factor .... 1.0\n",
      "[2022-12-16 13:29:35,625] [INFO] [config.py:1024:print]   initial_dynamic_scale ........ 65536\n",
      "[2022-12-16 13:29:35,625] [INFO] [config.py:1024:print]   load_universal_checkpoint .... False\n",
      "[2022-12-16 13:29:35,625] [INFO] [config.py:1024:print]   loss_scale ................... 0\n",
      "[2022-12-16 13:29:35,626] [INFO] [config.py:1024:print]   memory_breakdown ............. False\n",
      "[2022-12-16 13:29:35,626] [INFO] [config.py:1024:print]   monitor_config ............... <deepspeed.monitor.config.DeepSpeedMonitorConfig object at 0x7fa7b1942520>\n",
      "[2022-12-16 13:29:35,627] [INFO] [config.py:1024:print]   nebula_config ................ {\n",
      "    \"enabled\": false, \n",
      "    \"persistent_storage_path\": null, \n",
      "    \"persistent_time_interval\": 100, \n",
      "    \"num_of_version_in_retention\": 2, \n",
      "    \"enable_nebula_load\": true, \n",
      "    \"load_path\": null\n",
      "}\n",
      "[2022-12-16 13:29:35,627] [INFO] [config.py:1024:print]   optimizer_legacy_fusion ...... False\n",
      "[2022-12-16 13:29:35,627] [INFO] [config.py:1024:print]   optimizer_name ............... adamw\n",
      "[2022-12-16 13:29:35,628] [INFO] [config.py:1024:print]   optimizer_params ............. {'lr': 1e-05, 'betas': [0.9, 0.999], 'eps': 1e-08, 'weight_decay': 0.0}\n",
      "[2022-12-16 13:29:35,628] [INFO] [config.py:1024:print]   pipeline ..................... {'stages': 'auto', 'partition': 'best', 'seed_layers': False, 'activation_checkpoint_interval': 0}\n",
      "[2022-12-16 13:29:35,628] [INFO] [config.py:1024:print]   pld_enabled .................. False\n",
      "[2022-12-16 13:29:35,629] [INFO] [config.py:1024:print]   pld_params ................... False\n",
      "[2022-12-16 13:29:35,629] [INFO] [config.py:1024:print]   prescale_gradients ........... False\n",
      "[2022-12-16 13:29:35,630] [INFO] [config.py:1024:print]   scheduler_name ............... WarmupLR\n",
      "[2022-12-16 13:29:35,630] [INFO] [config.py:1024:print]   scheduler_params ............. {'warmup_min_lr': 0, 'warmup_max_lr': 1e-05, 'warmup_num_steps': 100}\n",
      "[2022-12-16 13:29:35,630] [INFO] [config.py:1024:print]   sparse_attention ............. None\n",
      "[2022-12-16 13:29:35,631] [INFO] [config.py:1024:print]   sparse_gradients_enabled ..... False\n",
      "[2022-12-16 13:29:35,631] [INFO] [config.py:1024:print]   steps_per_print .............. 10\n",
      "[2022-12-16 13:29:35,631] [INFO] [config.py:1024:print]   train_batch_size ............. 64\n",
      "[2022-12-16 13:29:35,632] [INFO] [config.py:1024:print]   train_micro_batch_size_per_gpu  32\n",
      "[2022-12-16 13:29:35,632] [INFO] [config.py:1024:print]   use_node_local_storage ....... False\n",
      "[2022-12-16 13:29:35,633] [INFO] [config.py:1024:print]   wall_clock_breakdown ......... False\n",
      "[2022-12-16 13:29:35,633] [INFO] [config.py:1024:print]   world_size ................... 1\n",
      "[2022-12-16 13:29:35,633] [INFO] [config.py:1024:print]   zero_allow_untested_optimizer  False\n",
      "[2022-12-16 13:29:35,634] [INFO] [config.py:1024:print]   zero_config .................. stage=2 contiguous_gradients=True reduce_scatter=True reduce_bucket_size=200000000 allgather_partitions=True allgather_bucket_size=200000000 overlap_comm=True load_from_fp32_weights=True elastic_checkpoint=False offload_param=None offload_optimizer=DeepSpeedZeroOffloadOptimizerConfig(device='cpu', nvme_path=None, buffer_count=4, pin_memory=True, pipeline=False, pipeline_read=False, pipeline_write=False, fast_init=False) sub_group_size=1,000,000,000 cpu_offload_param=None cpu_offload_use_pin_memory=None cpu_offload=None prefetch_bucket_size=50,000,000 param_persistence_threshold=100,000 model_persistence_threshold=sys.maxsize max_live_parameters=1,000,000,000 max_reuse_distance=1,000,000,000 gather_16bit_weights_on_model_save=False stage3_gather_fp16_weights_on_model_save=False ignore_unused_parameters=True legacy_stage1=False round_robin_gradients=False\n",
      "[2022-12-16 13:29:35,634] [INFO] [config.py:1024:print]   zero_enabled ................. True\n",
      "[2022-12-16 13:29:35,635] [INFO] [config.py:1024:print]   zero_optimization_stage ...... 2\n",
      "[2022-12-16 13:29:35,635] [INFO] [config.py:1009:print_user_config]   json = {\n",
      "    \"fp16\": {\n",
      "        \"enabled\": true, \n",
      "        \"loss_scale\": 0, \n",
      "        \"loss_scale_window\": 1000, \n",
      "        \"initial_scale_power\": 16, \n",
      "        \"hysteresis\": 2, \n",
      "        \"min_loss_scale\": 1\n",
      "    }, \n",
      "    \"optimizer\": {\n",
      "        \"type\": \"AdamW\", \n",
      "        \"params\": {\n",
      "            \"lr\": 1e-05, \n",
      "            \"betas\": [0.9, 0.999], \n",
      "            \"eps\": 1e-08, \n",
      "            \"weight_decay\": 0.0\n",
      "        }\n",
      "    }, \n",
      "    \"scheduler\": {\n",
      "        \"type\": \"WarmupLR\", \n",
      "        \"params\": {\n",
      "            \"warmup_min_lr\": 0, \n",
      "            \"warmup_max_lr\": 1e-05, \n",
      "            \"warmup_num_steps\": 100\n",
      "        }\n",
      "    }, \n",
      "    \"zero_optimization\": {\n",
      "        \"stage\": 2, \n",
      "        \"offload_optimizer\": {\n",
      "            \"device\": \"cpu\", \n",
      "            \"pin_memory\": true\n",
      "        }, \n",
      "        \"allgather_partitions\": true, \n",
      "        \"allgather_bucket_size\": 2.000000e+08, \n",
      "        \"overlap_comm\": true, \n",
      "        \"reduce_scatter\": true, \n",
      "        \"reduce_bucket_size\": 2.000000e+08, \n",
      "        \"contiguous_gradients\": true\n",
      "    }, \n",
      "    \"gradient_accumulation_steps\": 2, \n",
      "    \"gradient_clipping\": 1.0, \n",
      "    \"train_batch_size\": 64, \n",
      "    \"train_micro_batch_size_per_gpu\": 32\n",
      "}\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using /home/ubuntu/.cache/torch_extensions/py38_cu117 as PyTorch extensions root...\n",
      "No modifications detected for re-loaded extension module utils, skipping build step...\n",
      "Loading extension module utils...\n",
      "***** Running training *****\n",
      "  Num examples = 64000\n",
      "  Num Epochs = 9223372036854775807\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Time to load utils op: 0.005568742752075195 seconds\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  Instantaneous batch size per device = 32\n",
      "  Total train batch size (w. parallel, distributed & accumulation) = 64\n",
      "  Gradient Accumulation steps = 2\n",
      "  Total optimization steps = 1000\n",
      "  Number of trainable parameters = 1543304960\n",
      "Reading metadata...: 2165it [00:00, 64424.75it/s]\n",
      "The following columns in the training set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: sentence, audio, input_length. If sentence, audio, input_length are not expected by `WhisperForConditionalGeneration.forward`,  you can safely ignore this message.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2022-12-16 13:30:12,371] [INFO] [stage_1_and_2.py:1765:step] [deepspeed] OVERFLOW! Rank 0 Skipping step. Attempted loss scale: 65536, reducing to 65536\n"
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       "      [ 101/1000 24:25 < 3:41:52, 0.07 it/s, Epoch 0.10/9223372036854775807]\n",
       "    </div>\n",
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       "      <th>Step</th>\n",
       "      <th>Training Loss</th>\n",
       "      <th>Validation Loss</th>\n",
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      "[2022-12-16 13:30:26,874] [INFO] [stage_1_and_2.py:1765:step] [deepspeed] OVERFLOW! Rank 0 Skipping step. Attempted loss scale: 65536, reducing to 32768.0\n",
      "[2022-12-16 13:30:26,878] [INFO] [timer.py:197:stop] 0/4, RunningAvgSamplesPerSec=6.359143267427371, CurrSamplesPerSec=6.05562698727593, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:30:41,688] [INFO] [stage_1_and_2.py:1765:step] [deepspeed] OVERFLOW! Rank 0 Skipping step. Attempted loss scale: 32768.0, reducing to 16384.0\n",
      "[2022-12-16 13:30:41,692] [INFO] [timer.py:197:stop] 0/6, RunningAvgSamplesPerSec=6.442681205426282, CurrSamplesPerSec=6.185670974618687, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:30:56,690] [INFO] [timer.py:197:stop] 0/8, RunningAvgSamplesPerSec=6.250138482974161, CurrSamplesPerSec=5.239387620689085, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:31:11,390] [INFO] [timer.py:197:stop] 0/10, RunningAvgSamplesPerSec=6.199217766209486, CurrSamplesPerSec=5.469275533253204, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:31:25,760] [INFO] [timer.py:197:stop] 0/12, RunningAvgSamplesPerSec=6.187350055236473, CurrSamplesPerSec=5.465893137251788, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:31:40,116] [INFO] [timer.py:197:stop] 0/14, RunningAvgSamplesPerSec=6.182433423403349, CurrSamplesPerSec=5.578369458479616, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:31:54,845] [INFO] [timer.py:197:stop] 0/16, RunningAvgSamplesPerSec=6.168209488109452, CurrSamplesPerSec=5.481925126875305, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:32:09,837] [INFO] [timer.py:197:stop] 0/18, RunningAvgSamplesPerSec=6.166182771011467, CurrSamplesPerSec=5.576634147245411, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:32:24,514] [INFO] [logging.py:68:log_dist] [Rank 0] step=10, skipped=3, lr=[4.225490200071284e-06], mom=[[0.9, 0.999]]\n",
      "[2022-12-16 13:32:24,516] [INFO] [timer.py:197:stop] 0/20, RunningAvgSamplesPerSec=6.14923830606697, CurrSamplesPerSec=5.4862895214102165, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:32:39,349] [INFO] [timer.py:197:stop] 0/22, RunningAvgSamplesPerSec=6.1362626639738735, CurrSamplesPerSec=5.400516433628815, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:32:54,284] [INFO] [timer.py:197:stop] 0/24, RunningAvgSamplesPerSec=6.116244939022191, CurrSamplesPerSec=5.331918879729864, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:33:09,152] [INFO] [timer.py:197:stop] 0/26, RunningAvgSamplesPerSec=6.111198466738003, CurrSamplesPerSec=5.46965978645552, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:33:24,156] [INFO] [timer.py:197:stop] 0/28, RunningAvgSamplesPerSec=6.1089592602745295, CurrSamplesPerSec=5.493128255256428, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:33:39,020] [INFO] [timer.py:197:stop] 0/30, RunningAvgSamplesPerSec=6.107566100664851, CurrSamplesPerSec=5.454037094012864, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:33:53,833] [INFO] [timer.py:197:stop] 0/32, RunningAvgSamplesPerSec=6.104934863126791, CurrSamplesPerSec=5.402098409851611, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:34:08,846] [INFO] [timer.py:197:stop] 0/34, RunningAvgSamplesPerSec=6.106360932585499, CurrSamplesPerSec=5.522979183752241, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:34:23,904] [INFO] [timer.py:197:stop] 0/36, RunningAvgSamplesPerSec=6.1056306050274625, CurrSamplesPerSec=5.534223579655121, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:34:38,360] [INFO] [timer.py:197:stop] 0/38, RunningAvgSamplesPerSec=6.107025499795947, CurrSamplesPerSec=5.517999025063001, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:34:52,987] [INFO] [logging.py:68:log_dist] [Rank 0] step=20, skipped=3, lr=[6.15224460689137e-06], mom=[[0.9, 0.999]]\n",
      "[2022-12-16 13:34:52,989] [INFO] [timer.py:197:stop] 0/40, RunningAvgSamplesPerSec=6.106790407037756, CurrSamplesPerSec=5.482855146086943, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:35:07,678] [INFO] [timer.py:197:stop] 0/42, RunningAvgSamplesPerSec=6.106137329541975, CurrSamplesPerSec=5.49275126263391, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:35:22,387] [INFO] [timer.py:197:stop] 0/44, RunningAvgSamplesPerSec=6.101678041171418, CurrSamplesPerSec=5.378597132969251, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:35:36,795] [INFO] [timer.py:197:stop] 0/46, RunningAvgSamplesPerSec=6.09914148974474, CurrSamplesPerSec=5.4613528889589125, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:35:51,434] [INFO] [timer.py:197:stop] 0/48, RunningAvgSamplesPerSec=6.099051394709131, CurrSamplesPerSec=5.4884021703559025, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:36:05,840] [INFO] [timer.py:197:stop] 0/50, RunningAvgSamplesPerSec=6.100214513297745, CurrSamplesPerSec=5.47020037322054, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:36:20,385] [INFO] [timer.py:197:stop] 0/52, RunningAvgSamplesPerSec=6.098726784398205, CurrSamplesPerSec=5.433712844102512, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:36:35,297] [INFO] [timer.py:197:stop] 0/54, RunningAvgSamplesPerSec=6.0936261097499305, CurrSamplesPerSec=5.489423519383715, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:36:50,352] [INFO] [timer.py:197:stop] 0/56, RunningAvgSamplesPerSec=6.0895209772752175, CurrSamplesPerSec=5.477875509886321, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:37:05,025] [INFO] [timer.py:197:stop] 0/58, RunningAvgSamplesPerSec=6.0909453489179874, CurrSamplesPerSec=5.569184849154154, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:37:20,470] [INFO] [logging.py:68:log_dist] [Rank 0] step=30, skipped=3, lr=[7.156818820794936e-06], mom=[[0.9, 0.999]]\n",
      "[2022-12-16 13:37:20,471] [INFO] [timer.py:197:stop] 0/60, RunningAvgSamplesPerSec=6.091265755090447, CurrSamplesPerSec=5.483664270842526, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:37:35,692] [INFO] [timer.py:197:stop] 0/62, RunningAvgSamplesPerSec=6.090134375608421, CurrSamplesPerSec=5.589692236464059, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:37:50,466] [INFO] [timer.py:197:stop] 0/64, RunningAvgSamplesPerSec=6.087445931775481, CurrSamplesPerSec=5.484206733168804, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:38:05,662] [INFO] [timer.py:197:stop] 0/66, RunningAvgSamplesPerSec=6.085481288319546, CurrSamplesPerSec=5.456354321207382, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:38:20,812] [INFO] [timer.py:197:stop] 0/68, RunningAvgSamplesPerSec=6.0849633855165886, CurrSamplesPerSec=5.560404510325844, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:38:35,454] [INFO] [timer.py:197:stop] 0/70, RunningAvgSamplesPerSec=6.082841357920188, CurrSamplesPerSec=5.466938858736218, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:38:50,590] [INFO] [timer.py:197:stop] 0/72, RunningAvgSamplesPerSec=6.081021514785823, CurrSamplesPerSec=5.512498905449392, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:39:05,062] [INFO] [timer.py:197:stop] 0/74, RunningAvgSamplesPerSec=6.081159270273127, CurrSamplesPerSec=5.590209079941052, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:39:19,759] [INFO] [timer.py:197:stop] 0/76, RunningAvgSamplesPerSec=6.082366611952337, CurrSamplesPerSec=5.557982892618384, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:39:34,541] [INFO] [timer.py:197:stop] 0/78, RunningAvgSamplesPerSec=6.0817232366484815, CurrSamplesPerSec=5.549053124586951, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:39:49,756] [INFO] [logging.py:68:log_dist] [Rank 0] step=40, skipped=3, lr=[7.841008620334974e-06], mom=[[0.9, 0.999]]\n",
      "[2022-12-16 13:39:49,758] [INFO] [timer.py:197:stop] 0/80, RunningAvgSamplesPerSec=6.077909701875687, CurrSamplesPerSec=5.460640310175479, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:40:04,561] [INFO] [timer.py:197:stop] 0/82, RunningAvgSamplesPerSec=6.0782675124530545, CurrSamplesPerSec=5.539460325595526, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:40:19,768] [INFO] [timer.py:197:stop] 0/84, RunningAvgSamplesPerSec=6.078390170810889, CurrSamplesPerSec=5.471118389391574, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:40:34,291] [INFO] [timer.py:197:stop] 0/86, RunningAvgSamplesPerSec=6.0795061630666805, CurrSamplesPerSec=5.454458221341045, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:40:49,017] [INFO] [timer.py:197:stop] 0/88, RunningAvgSamplesPerSec=6.07951693722567, CurrSamplesPerSec=5.479403593034189, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:41:04,035] [INFO] [timer.py:197:stop] 0/90, RunningAvgSamplesPerSec=6.07713721760037, CurrSamplesPerSec=5.456287998666598, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:41:18,947] [INFO] [timer.py:197:stop] 0/92, RunningAvgSamplesPerSec=6.077188149302228, CurrSamplesPerSec=5.50184879924073, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:41:33,488] [INFO] [timer.py:197:stop] 0/94, RunningAvgSamplesPerSec=6.07680443723328, CurrSamplesPerSec=5.473631408915449, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:41:47,873] [INFO] [timer.py:197:stop] 0/96, RunningAvgSamplesPerSec=6.078162490871368, CurrSamplesPerSec=5.581634406904709, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:42:02,601] [INFO] [timer.py:197:stop] 0/98, RunningAvgSamplesPerSec=6.07918864648028, CurrSamplesPerSec=5.5189762738392805, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:42:17,393] [INFO] [logging.py:68:log_dist] [Rank 0] step=50, skipped=3, lr=[8.360489289678585e-06], mom=[[0.9, 0.999]]\n",
      "[2022-12-16 13:42:17,394] [INFO] [timer.py:197:stop] 0/100, RunningAvgSamplesPerSec=6.079721917832034, CurrSamplesPerSec=5.565398772008929, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:42:32,340] [INFO] [timer.py:197:stop] 0/102, RunningAvgSamplesPerSec=6.079079748095393, CurrSamplesPerSec=5.53473523707476, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:42:46,647] [INFO] [timer.py:197:stop] 0/104, RunningAvgSamplesPerSec=6.080121170095116, CurrSamplesPerSec=5.546972622941274, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:43:01,497] [INFO] [timer.py:197:stop] 0/106, RunningAvgSamplesPerSec=6.080171891208223, CurrSamplesPerSec=5.554791525418257, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:43:16,886] [INFO] [timer.py:197:stop] 0/108, RunningAvgSamplesPerSec=6.081835087987497, CurrSamplesPerSec=5.58878961931587, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:43:31,557] [INFO] [timer.py:197:stop] 0/110, RunningAvgSamplesPerSec=6.081642070013767, CurrSamplesPerSec=5.4866510488093745, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:43:46,623] [INFO] [timer.py:197:stop] 0/112, RunningAvgSamplesPerSec=6.081178765969859, CurrSamplesPerSec=5.503815912407227, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:44:01,079] [INFO] [timer.py:197:stop] 0/114, RunningAvgSamplesPerSec=6.081720835190203, CurrSamplesPerSec=5.504593308578239, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:44:16,482] [INFO] [timer.py:197:stop] 0/116, RunningAvgSamplesPerSec=6.080214101573954, CurrSamplesPerSec=5.447973428766622, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:44:30,878] [INFO] [timer.py:197:stop] 0/118, RunningAvgSamplesPerSec=6.080946889626902, CurrSamplesPerSec=5.482487848212496, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:44:45,818] [INFO] [logging.py:68:log_dist] [Rank 0] step=60, skipped=3, lr=[8.779374278362457e-06], mom=[[0.9, 0.999]]\n",
      "[2022-12-16 13:44:45,820] [INFO] [timer.py:197:stop] 0/120, RunningAvgSamplesPerSec=6.079880158785482, CurrSamplesPerSec=5.410680853516901, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:45:00,308] [INFO] [timer.py:197:stop] 0/122, RunningAvgSamplesPerSec=6.0800487826701, CurrSamplesPerSec=5.51626365654903, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:45:14,816] [INFO] [timer.py:197:stop] 0/124, RunningAvgSamplesPerSec=6.079264706998162, CurrSamplesPerSec=5.5087795351327316, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:45:29,834] [INFO] [timer.py:197:stop] 0/126, RunningAvgSamplesPerSec=6.079846025945439, CurrSamplesPerSec=5.4936159271225256, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:45:44,851] [INFO] [timer.py:197:stop] 0/128, RunningAvgSamplesPerSec=6.078175014056017, CurrSamplesPerSec=5.362789672759209, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:45:59,717] [INFO] [timer.py:197:stop] 0/130, RunningAvgSamplesPerSec=6.079084147393918, CurrSamplesPerSec=5.541067573145952, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:46:14,797] [INFO] [timer.py:197:stop] 0/132, RunningAvgSamplesPerSec=6.078861152800443, CurrSamplesPerSec=5.477529668210021, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:46:29,130] [INFO] [timer.py:197:stop] 0/134, RunningAvgSamplesPerSec=6.080307858784291, CurrSamplesPerSec=5.559784456324279, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:46:44,072] [INFO] [timer.py:197:stop] 0/136, RunningAvgSamplesPerSec=6.07930472994486, CurrSamplesPerSec=5.580544815418963, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:46:58,724] [INFO] [timer.py:197:stop] 0/138, RunningAvgSamplesPerSec=6.078143442074857, CurrSamplesPerSec=5.314022303909574, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:47:13,565] [INFO] [logging.py:68:log_dist] [Rank 0] step=70, skipped=3, lr=[9.130374013504131e-06], mom=[[0.9, 0.999]]\n",
      "[2022-12-16 13:47:13,567] [INFO] [timer.py:197:stop] 0/140, RunningAvgSamplesPerSec=6.077773018304035, CurrSamplesPerSec=5.36396394293752, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:47:28,585] [INFO] [timer.py:197:stop] 0/142, RunningAvgSamplesPerSec=6.077639901148956, CurrSamplesPerSec=5.461940956484987, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:47:43,370] [INFO] [timer.py:197:stop] 0/144, RunningAvgSamplesPerSec=6.078145299833403, CurrSamplesPerSec=5.518752068230726, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:47:58,138] [INFO] [timer.py:197:stop] 0/146, RunningAvgSamplesPerSec=6.077895578341843, CurrSamplesPerSec=5.5512169228705694, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:48:13,249] [INFO] [timer.py:197:stop] 0/148, RunningAvgSamplesPerSec=6.077814599805705, CurrSamplesPerSec=5.491996533706707, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:48:27,903] [INFO] [timer.py:197:stop] 0/150, RunningAvgSamplesPerSec=6.076902008713945, CurrSamplesPerSec=5.332959519203826, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:48:42,061] [INFO] [timer.py:197:stop] 0/152, RunningAvgSamplesPerSec=6.0783920477415, CurrSamplesPerSec=5.55632004431884, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:48:56,535] [INFO] [timer.py:197:stop] 0/154, RunningAvgSamplesPerSec=6.078732911919996, CurrSamplesPerSec=5.458582053389676, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:49:11,153] [INFO] [timer.py:197:stop] 0/156, RunningAvgSamplesPerSec=6.079008773246385, CurrSamplesPerSec=5.543700002028015, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:49:25,910] [INFO] [timer.py:197:stop] 0/158, RunningAvgSamplesPerSec=6.077901196166508, CurrSamplesPerSec=5.497338259422809, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:49:41,537] [INFO] [logging.py:68:log_dist] [Rank 0] step=80, skipped=3, lr=[9.432453625862409e-06], mom=[[0.9, 0.999]]\n",
      "[2022-12-16 13:49:41,538] [INFO] [timer.py:197:stop] 0/160, RunningAvgSamplesPerSec=6.076246622231216, CurrSamplesPerSec=5.371769954520086, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:49:56,401] [INFO] [timer.py:197:stop] 0/162, RunningAvgSamplesPerSec=6.076453900936628, CurrSamplesPerSec=5.506221269741678, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:50:10,825] [INFO] [timer.py:197:stop] 0/164, RunningAvgSamplesPerSec=6.077190405328247, CurrSamplesPerSec=5.540300881158864, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:50:26,051] [INFO] [timer.py:197:stop] 0/166, RunningAvgSamplesPerSec=6.077041030460407, CurrSamplesPerSec=5.509338737628304, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:50:40,658] [INFO] [timer.py:197:stop] 0/168, RunningAvgSamplesPerSec=6.077215911476895, CurrSamplesPerSec=5.465386561501869, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:50:55,458] [INFO] [timer.py:197:stop] 0/170, RunningAvgSamplesPerSec=6.078024759766047, CurrSamplesPerSec=5.50886816782787, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:51:10,316] [INFO] [timer.py:197:stop] 0/172, RunningAvgSamplesPerSec=6.077383165843686, CurrSamplesPerSec=5.523170094873224, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:51:25,012] [INFO] [timer.py:197:stop] 0/174, RunningAvgSamplesPerSec=6.077781559393984, CurrSamplesPerSec=5.523025319397122, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:51:39,852] [INFO] [timer.py:197:stop] 0/176, RunningAvgSamplesPerSec=6.078433625571553, CurrSamplesPerSec=5.568140074904409, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:51:54,462] [INFO] [timer.py:197:stop] 0/178, RunningAvgSamplesPerSec=6.077703528416714, CurrSamplesPerSec=5.485578492081232, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:52:10,224] [INFO] [logging.py:68:log_dist] [Rank 0] step=90, skipped=3, lr=[9.697596263093091e-06], mom=[[0.9, 0.999]]\n",
      "[2022-12-16 13:52:10,225] [INFO] [timer.py:197:stop] 0/180, RunningAvgSamplesPerSec=6.078332169068046, CurrSamplesPerSec=5.557059195233783, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:52:24,902] [INFO] [timer.py:197:stop] 0/182, RunningAvgSamplesPerSec=6.077463728768749, CurrSamplesPerSec=5.458477050176381, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:52:40,291] [INFO] [timer.py:197:stop] 0/184, RunningAvgSamplesPerSec=6.076290749991055, CurrSamplesPerSec=5.492102156302423, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:52:54,947] [INFO] [timer.py:197:stop] 0/186, RunningAvgSamplesPerSec=6.07565767596194, CurrSamplesPerSec=5.388023243640082, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:53:09,877] [INFO] [timer.py:197:stop] 0/188, RunningAvgSamplesPerSec=6.075693478896997, CurrSamplesPerSec=5.5255764788423285, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:53:24,501] [INFO] [timer.py:197:stop] 0/190, RunningAvgSamplesPerSec=6.0754839341391245, CurrSamplesPerSec=5.539336641858779, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:53:38,944] [INFO] [timer.py:197:stop] 0/192, RunningAvgSamplesPerSec=6.075775207227371, CurrSamplesPerSec=5.469889160531412, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:53:53,465] [INFO] [timer.py:197:stop] 0/194, RunningAvgSamplesPerSec=6.075782725725061, CurrSamplesPerSec=5.488814031317932, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:54:08,605] [INFO] [timer.py:197:stop] 0/196, RunningAvgSamplesPerSec=6.075932541941936, CurrSamplesPerSec=5.513335374613696, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:54:23,298] [INFO] [timer.py:197:stop] 0/198, RunningAvgSamplesPerSec=6.076327542642147, CurrSamplesPerSec=5.506319307844521, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n",
      "[2022-12-16 13:54:38,322] [INFO] [logging.py:68:log_dist] [Rank 0] step=100, skipped=3, lr=[9.933858671331224e-06], mom=[[0.9, 0.999]]\n",
      "[2022-12-16 13:54:38,323] [INFO] [timer.py:197:stop] 0/200, RunningAvgSamplesPerSec=6.07605192544789, CurrSamplesPerSec=5.413820537564129, MemAllocated=3.0GB, MaxMemAllocated=19.53GB\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "***** Running Evaluation *****\n",
      "  Num examples: Unknown\n",
      "  Batch size = 8\n",
      "Reading metadata...: 1704it [00:00, 13668.60it/s]\n",
      "The following columns in the evaluation set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: sentence, audio, input_length. If sentence, audio, input_length are not expected by `WhisperForConditionalGeneration.forward`,  you can safely ignore this message.\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "/home/ubuntu/.local/lib/python3.8/site-packages/transformers/generation/utils.py:1134: UserWarning: You have modified the pretrained model configuration to control generation. This is a deprecated strategy to control generation and will be removed soon, in a future version. Please use a generation configuration file (see https://huggingface.co/docs/transformers/main_classes/text_generation)\n",
      "  warnings.warn(\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n",
      "Generate config GenerationConfig {\n",
      "  \"begin_suppress_tokens\": [\n",
      "    220,\n",
      "    50257\n",
      "  ],\n",
      "  \"bos_token_id\": 50257,\n",
      "  \"decoder_start_token_id\": 50258,\n",
      "  \"eos_token_id\": 50257,\n",
      "  \"max_length\": 448,\n",
      "  \"pad_token_id\": 50257,\n",
      "  \"suppress_tokens\": [],\n",
      "  \"transformers_version\": \"4.26.0.dev0\",\n",
      "  \"use_cache\": false\n",
      "}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "trainer.train()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "810ced54-7187-4a06-b2fe-ba6dcca94dc3",
   "metadata": {
    "id": "810ced54-7187-4a06-b2fe-ba6dcca94dc3"
   },
   "source": [
    "We can label our checkpoint with the `whisper-event` tag on push by setting the appropriate key-word arguments (kwargs):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c704f91e-241b-48c9-b8e0-f0da396a9663",
   "metadata": {
    "id": "c704f91e-241b-48c9-b8e0-f0da396a9663"
   },
   "outputs": [],
   "source": [
    "kwargs = {\n",
    "    \"dataset_tags\": dataset_names,\n",
    "    \"dataset\": \"Common Voice 11.0, FB Voxpopuli, Google FLEURS\",  # a 'pretty' name for the training dataset\n",
    "    \"language\": \"fi\",\n",
    "    \"model_name\": \"Whisper Large Fi - Sormunen Teemu\",  # a 'pretty' name for your model\n",
    "    \"finetuned_from\": \"openai/whisper-large\",\n",
    "    \"tasks\": \"automatic-speech-recognition\",\n",
    "    \"tags\": \"whisper-event\",\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "090d676a-f944-4297-a938-a40eda0b2b68",
   "metadata": {
    "id": "090d676a-f944-4297-a938-a40eda0b2b68"
   },
   "source": [
    "The training results can now be uploaded to the Hub. To do so, execute the `push_to_hub` command and save the preprocessor object we created:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d7030622-caf7-4039-939b-6195cdaa2585",
   "metadata": {
    "id": "d7030622-caf7-4039-939b-6195cdaa2585"
   },
   "outputs": [],
   "source": [
    "trainer.push_to_hub(**kwargs)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca743fbd-602c-48d4-ba8d-a2fe60af64ba",
   "metadata": {
    "id": "ca743fbd-602c-48d4-ba8d-a2fe60af64ba"
   },
   "source": [
    "## Closing Remarks"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f737783-2870-4e35-aa11-86a42d7d997a",
   "metadata": {
    "id": "7f737783-2870-4e35-aa11-86a42d7d997a"
   },
   "source": [
    "In this blog, we covered a step-by-step guide on fine-tuning Whisper for multilingual ASR \n",
    "using 🤗 Datasets, Transformers and the Hugging Face Hub. For more details on the Whisper model, the Common Voice dataset and the theory behind fine-tuning, refere to the accompanying [blog post](https://huggingface.co/blog/fine-tune-whisper). If you're interested in fine-tuning other \n",
    "Transformers models, both for English and multilingual ASR, be sure to check out the \n",
    "examples scripts at [examples/pytorch/speech-recognition](https://github.com/huggingface/transformers/tree/main/examples/pytorch/speech-recognition)."
   ]
  }
 ],
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