{ "cells": [ { "cell_type": "markdown", "metadata": { "id": "mp1iisL6cQJ3" }, "source": [ "# Idea - (EN)\n", "\n", "The idea is to be able to obtain a trained model using the family of T5 that allow us to parametrize the generation of texts.\n", "\n", "Usually we will train using the text of poems, then we provide an starting text and obtain the generated one.\n", "\n", "In this case we want to provide some parameters to control a the generation, if it is possible 😀\n", "\n", "At the beginning the parameter can be the author, with the goal of generate text according to the style of the author.\n", "\n", "Something like this:\n", "\n", "```poema: estilo: && texto: ```\n", "\n", "If we manage to achieve this 🤞, then we can add more parameters like the sentiment that we want to obtain in the generated text, and some words that we want to include in the poem.\n", "\n", "To be able to include more parameters we will need to add more information to the dataset like sentiment expressed and keywords." ] }, { "cell_type": "markdown", "metadata": { "id": "-vNsr0_4fkTO" }, "source": [ "# Idea - (ES)\n", "\n", "La idea es poder obtener un modelo entrenado usando la familia T5 que nos permita parametrizar la generación de los textos.\n", "\n", "Usualmente entrenamos usando los textos de los poemas, luego proveemos un texto inicial y de este el modelo obtenemos los textos generados.\n", "\n", "En este caso vamos a proveer algunos parámetros para controlar la generación, si es posible 😀\n", "\n", "Al inicio el parámetro puede ser el autor, con el objetivo de generar texto de acuerdo al estilo del autor.\n", "\n", "Algo como esto:\n", "\n", "```poema: estilo: && texto: ```\n", "\n", "Si logramos alcanzar esto 🤞, entonces podemos adicionar más parámetros como el sentimiento que queremos obtener en el texto generado, y algunas palabras que queremos que estén incluidas en el poema.\n", "\n", "Para poder incluir más parámetros vamos a necesitar adicionar más información al dataset, sobre el sentimiento expresado y palabras claves." ] }, { "cell_type": "markdown", "metadata": { "id": "nZt0MLPTOHRd" }, "source": [ "# Install dependencies" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "id": "T7lhH5rIN-fE" }, "outputs": [], "source": [ "!pip install -q transformers datasets sentencepiece" ] }, { "cell_type": "markdown", "metadata": { "id": "K67QVgrYOYsa" }, "source": [ "# Check GPU" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "DvSSkbtUObMw", "outputId": "24a30f54-0252-4909-b7e9-371cd6ee2da3" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Wed Mar 16 11:32:32 2022 \n", "+-----------------------------------------------------------------------------+\n", "| NVIDIA-SMI 460.32.03 Driver Version: 460.32.03 CUDA Version: 11.2 |\n", "|-------------------------------+----------------------+----------------------+\n", "| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n", "| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n", "| | | MIG M. |\n", "|===============================+======================+======================|\n", "| 0 Tesla P100-PCIE... Off | 00000000:00:04.0 Off | 0 |\n", "| N/A 41C P0 27W / 250W | 0MiB / 16280MiB | 0% Default |\n", "| | | N/A |\n", "+-------------------------------+----------------------+----------------------+\n", " \n", "+-----------------------------------------------------------------------------+\n", "| Processes: |\n", "| GPU GI CI PID Type Process name GPU Memory |\n", "| ID ID Usage |\n", "|=============================================================================|\n", "| No running processes found |\n", "+-----------------------------------------------------------------------------+\n" ] } ], "source": [ "!nvidia-smi " ] }, { "cell_type": "markdown", "metadata": { "id": "aFdrElPnOk3D" }, "source": [ "## Free GPU" ] }, { "cell_type": "markdown", "metadata": { "id": "LZW32TnDNnS2" }, "source": [ "In case the GPU memory give you issues with memory space allocation, this cell can help you.\n", "\n", "If repeteadly appears the problem, you will need to `Runtime > Restart runtime`. \n", "Try to lower the batch size in the TrainingArguments or activate the gradient_checkpointing to lower the required memory during training. \n", "\n", "The gradient_checkpointing will add more time to the computation. Some articles mention an overhead of 20%. " ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "id": "RNkqL8HLOpDT" }, "outputs": [], "source": [ "import torch, gc\n", "gc.collect()\n", "torch.cuda.empty_cache()" ] }, { "cell_type": "markdown", "metadata": { "id": "XcIgOWGQPMqG" }, "source": [ "# Parameters" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "id": "SALMoJJ8Ox3T" }, "outputs": [], "source": [ "#@title # Set global parameters\n", "\n", "sel_model_name = 't5-small' #@param ['milyiyo/poem-gen-t5-small', 'flax-community/spanish-t5-small', \"t5-small\", \"t5-base\", \"t5-larg\", \"t5-3b\", \"t5-11b\"]\n", "sel_num_train_epochs = 15 #@param {type:\"number\"}" ] }, { "cell_type": "markdown", "metadata": { "id": "Q_fSxwIgPV9t" }, "source": [ "# Download dataset" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "whK2vwnDPYIi", "outputId": "fe4c2bc4-6821-442a-9b1a-67bc39204291" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "--2022-03-16 11:32:51-- https://docs.google.com/uc?export=download&id=1Rqfa-qC3Nm8oOMfnKjZYu6TF7iNg3Ju7\n", "Resolving docs.google.com (docs.google.com)... 74.125.195.100, 74.125.195.138, 74.125.195.102, ...\n", "Connecting to docs.google.com (docs.google.com)|74.125.195.100|:443... connected.\n", "HTTP request sent, awaiting response... 303 See Other\n", "Location: https://doc-0s-4s-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/jagb31d4n9oluej1342h2s3s8dc9f81d/1647430350000/13706297538515163693/*/1Rqfa-qC3Nm8oOMfnKjZYu6TF7iNg3Ju7?e=download [following]\n", "Warning: wildcards not supported in HTTP.\n", "--2022-03-16 11:32:53-- https://doc-0s-4s-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/jagb31d4n9oluej1342h2s3s8dc9f81d/1647430350000/13706297538515163693/*/1Rqfa-qC3Nm8oOMfnKjZYu6TF7iNg3Ju7?e=download\n", "Resolving doc-0s-4s-docs.googleusercontent.com (doc-0s-4s-docs.googleusercontent.com)... 74.125.195.132, 2607:f8b0:400e:c09::84\n", "Connecting to doc-0s-4s-docs.googleusercontent.com (doc-0s-4s-docs.googleusercontent.com)|74.125.195.132|:443... connected.\n", "HTTP request sent, awaiting response... 200 OK\n", "Length: 5198384 (5.0M) [text/csv]\n", "Saving to: ‘poems.csv’\n", "\n", "poems.csv 100%[===================>] 4.96M --.-KB/s in 0.04s \n", "\n", "2022-03-16 11:32:53 (112 MB/s) - ‘poems.csv’ saved [5198384/5198384]\n", "\n" ] } ], "source": [ "! wget --no-check-certificate 'https://docs.google.com/uc?export=download&id=1Rqfa-qC3Nm8oOMfnKjZYu6TF7iNg3Ju7' -O poems.csv" ] }, { "cell_type": "markdown", "metadata": { "id": "I-wK7BXdQHAM" }, "source": [ "# Import dependencies" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "id": "6MLK679yQI9Z" }, "outputs": [], "source": [ "import pandas as pd\n", "import os\n", "import torch\n", "from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, Seq2SeqTrainingArguments, DataCollatorForSeq2Seq, Seq2SeqTrainer\n", "from datasets import load_dataset, Dataset, DatasetDict\n", "import time\n", "import math\n", "from pprint import pprint\n", "import warnings\n", "warnings.filterwarnings('ignore')" ] }, { "cell_type": "markdown", "metadata": { "id": "qT3dozNuQSwe" }, "source": [ "# Prepare dataset" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 289, "referenced_widgets": [ "a695d1e3bcdf4378bdcc69ba0712e261", "8269f12912dd4539a96567fb05924f02", "17b0a0883f2a48af9587a36005a75fce", "f4f860776d184ce69b46f3b806faa940", "4bc9ab6b9cf2457baf7f65ac2115b648", "c1f27492d2944f979b590daf7e639f3d", "765d0a88dbb84a8d9a62b3ff8114dabf", "89f7b79b219c4d358f28e13e8a75b1a7", "8110b2d3beb44e468b9e82a737984318", "d225203c4f824207876d21da99fcb912", "7b6bd4b2fb8d4873b061469aac8d40aa", "6c191438060147b1ba7ef9300a0bc2fe", "708c6d53fd46420c96e020def9929bb5", "1319f3edda2945498908622303dd82a6", "4a6b917e78d242aab12988be20504ba0", "bedbd03015c34478beaee32430a2cf52", "c54ed8d8fbe44132be352cb964f7bcf2", "f6e71874a7f74cafa510f7a8c40b5d6d", "4212addaba6249be807cd3a322854f5a", "bb3889e02ab5439595e6cfb886f30b57", "abd87a2c54064487a6e97d367349b3a8", "1bb1b49d4c4340c4978e6bfb01903e0a", "10f21010e84c4d8caf8ac9deed5d5960", "0d25e3a8b4f445a193af20fcba641879", "d039ec7b8df84558b560443e355d1854", "e20826620beb4813b348096f032757b3", "2bba75305cfc4eadb2d8837a32b66056", "d1f5906edce945c8a3667d9079c0eeb1", "ef9d9d128dc84d3094fc740a2ef9b674", "a8ad06e1446141fb98f4b11ce766da66", "93a03be76dcc417e87ab66603ae8ed40", "8554ac1b1d26412582df494f800b745f", "73c2a72bdcb747dab651b8ec5f36c5c1" ] }, "id": "e-lz3mOpQVDQ", "outputId": "37d45011-a9bd-4936-921e-4c82db0ec8f2" }, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "Using custom data configuration default-b2da644438462884\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Downloading and preparing dataset csv/default to /root/.cache/huggingface/datasets/csv/default-b2da644438462884/0.0.0/433e0ccc46f9880962cc2b12065189766fbb2bee57a221866138fb9203c83519...\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "Downloading data files: 0%| | 0/1 [00:00')\n", " content = content.replace('\\n', '')\n", " paragraphs = content.split('')\n", " res = []\n", "\n", " for i in range(0, len(paragraphs)-1, 2):\n", " res.append(paragraphs[i] + ' ' + paragraphs[i+1])\n", " i+=1\n", "\n", " paragraphs = res\n", "\n", " for i in range(len(paragraphs)-1):\n", " res_dict['paragraph'] += [paragraphs[i]]\n", " res_dict['author'] += [author]\n", " res_dict['generated'] += [paragraphs[i+1]]" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "AKYuGKBJR4rq", "outputId": "bdcc6bd2-0868-434d-8cfe-2688d7b63713" }, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "Dataset({\n", " features: ['paragraph', 'author', 'generated'],\n", " num_rows: 70386\n", "})" ] }, "metadata": {}, "execution_count": 27 } ], "source": [ "new_ds = Dataset.from_dict(res_dict)\n", "new_ds" ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "HZK8HmQKR-ap", "outputId": "1afde007-f417-40e6-a233-ad8ecc70cac8" }, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "{'author': 'Leopoldo Lugones',\n", " 'generated': 'Devana un ovillo de de bruma. El telar de la luna tiende en plata su urdimbre;',\n", " 'paragraph': 'Que con lánguidas brisas el cielo sahúma, El ciprés, como un huso,'}" ] }, "metadata": {}, "execution_count": 28 } ], "source": [ "new_ds[1]" ] }, { "cell_type": "markdown", "metadata": { "id": "gNfcbYcJSDGP" }, "source": [ "## Load model and tokenizer" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "id": "UdWxnJl3SGFh" }, "outputs": [], "source": [ "tokenizer = AutoTokenizer.from_pretrained(sel_model_name)\n", "model = AutoModelForSeq2SeqLM.from_pretrained(sel_model_name)" ] }, { "cell_type": "markdown", "metadata": { "id": "2zyqtqhjSUJu" }, "source": [ "## Tokenize dataset" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 118, "referenced_widgets": [ "e16b6317561045d5a83982e1002767d6", "f8d13f763d614d0984065db153f8b648", "9077d564756346e7b3b5241abcfa11c7", "1758b642dc554ef584f487a27ab7cb06", "b87d7e4aa48d44809ecfa27e84a50b42", "d88bdec6d90c4cf08292340c1d7d99be", "3cfc9df85e5640519c35a6732f590cb0", "8ddaab64af6146fb97fa0cee453ec1c6", "3cfd59d1059147e5a10a0c5a67edd59b", "7855ee2071c648acb4a75d9819a6a383", "c17452128ef9427dab5b5bedd358ba31" ] }, "id": "sWkgkeZrSX85", "outputId": "41b5388d-a0ae-435f-9999-3b5d879cc077" }, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ " 0%| | 0/70386 [00:00" ], "text/html": [ "\n", "
\n", " \n", " \n", " [1760/1760 00:33]\n", "
\n", " " ] }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "Perplexity: 60.06\n" ] } ], "source": [ "eval_results = trainer.evaluate()\n", "print(f\"Perplexity: {math.exp(eval_results['eval_loss']):.2f}\")" ] }, { "cell_type": "markdown", "metadata": { "id": "TYAFJkUuU26r" }, "source": [ "# Train the model" ] }, { "cell_type": "code", "execution_count": 43, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "w23o_m9gU6xS", "outputId": "d8d03398-dc8c-40d4-f832-e3cdee6e8b84" }, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "***** Running training *****\n", " Num examples = 63348\n", " Num Epochs = 15\n", " Instantaneous batch size per device = 4\n", " Total train batch size (w. parallel, distributed & accumulation) = 4\n", " Gradient Accumulation steps = 1\n", " Total optimization steps = 237555\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "\n", "
\n", " \n", " \n", " [237555/237555 5:22:17, Epoch 15/15]\n", "
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StepTraining LossValidation Loss
50003.5397003.347355
100003.4107003.225994
150003.3236003.141384
200003.2500003.088421
250003.2055003.046101
300003.1677003.005724
350003.1189002.978578
400003.0972002.953285
450003.0855002.931780
500003.0364002.912441
550003.0125002.896153
600002.9987002.881165
650002.9734002.867543
700002.9782002.856346
750002.9492002.844610
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1150002.8568002.785577
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1250002.8534002.773678
1300002.8563002.769563
1350002.8387002.766378
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1450002.8137002.761508
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1550002.8138002.754713
1600002.8098002.750640
1650002.7944002.747890
1700002.8090002.744287
1750002.7897002.743072
1800002.7955002.740253
1850002.7930002.740279
1900002.7980002.735130
1950002.7955002.735126
2000002.7850002.732946
2050002.7701002.732896
2100002.7744002.731692
2150002.7827002.729487
2200002.7793002.730292
2250002.7782002.729847
2300002.7762002.728877
2350002.7719002.729183

" ] }, "metadata": {} }, { "output_type": "stream", "name": "stderr", "text": [ "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "\n", "

\n", " \n", " \n", " [1760/1760 07:20]\n", "
\n", " " ] }, "metadata": {} }, { "output_type": "stream", "name": "stderr", "text": [ "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-5000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-5000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-5000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-5000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-5000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-5000/spiece.model\n", "tokenizer config file saved in poem-gen-t5-small_v1/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/spiece.model\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-10000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-10000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-10000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-10000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-10000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-10000/spiece.model\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-15000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-15000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-15000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-15000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-15000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-15000/spiece.model\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-20000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-20000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-20000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-20000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-20000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-20000/spiece.model\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-25000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-25000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-25000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-25000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-25000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-25000/spiece.model\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-30000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-30000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-30000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-30000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-30000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-30000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-5000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-35000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-35000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-35000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-35000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-35000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-35000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-10000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-40000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-40000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-40000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-40000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-40000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-40000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-15000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-45000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-45000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-45000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-45000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-45000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-45000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-20000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-50000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-50000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-50000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-50000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-50000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-50000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-25000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-55000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-55000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-55000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-55000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-55000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-55000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-30000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-60000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-60000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-60000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-60000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-60000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-60000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-35000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-65000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-65000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-65000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-65000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-65000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-65000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-40000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-70000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-70000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-70000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-70000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-70000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-70000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-45000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-75000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-75000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-75000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-75000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-75000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-75000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-50000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-80000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-80000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-80000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-80000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-80000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-80000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-55000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-85000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-85000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-85000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-85000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-85000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-85000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-60000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-90000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-90000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-90000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-90000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-90000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-90000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-65000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-95000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-95000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-95000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-95000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-95000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-95000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-70000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-100000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-100000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-100000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-100000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-100000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-100000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-75000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-105000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-105000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-105000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-105000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-105000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-105000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-80000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-110000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-110000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-110000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-110000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-110000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-110000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-85000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-115000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-115000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-115000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-115000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-115000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-115000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-90000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-120000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-120000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-120000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-120000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-120000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-120000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-95000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-125000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-125000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-125000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-125000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-125000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-125000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-100000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-130000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-130000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-130000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-130000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-130000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-130000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-105000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-135000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-135000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-135000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-135000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-135000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-135000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-110000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-140000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-140000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-140000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-140000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-140000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-140000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-115000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-145000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-145000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-145000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-145000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-145000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-145000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-120000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-150000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-150000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-150000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-150000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-150000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-150000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-125000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-155000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-155000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-155000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-155000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-155000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-155000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-130000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-160000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-160000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-160000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-160000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-160000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-160000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-135000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-165000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-165000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-165000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-165000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-165000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-165000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-140000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-170000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-170000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-170000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-170000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-170000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-170000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-145000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-175000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-175000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-175000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-175000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-175000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-175000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-150000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-180000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-180000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-180000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-180000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-180000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-180000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-155000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-185000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-185000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-185000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-185000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-185000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-185000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-160000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-190000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-190000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-190000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-190000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-190000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-190000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-165000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-195000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-195000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-195000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-195000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-195000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-195000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-170000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-200000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-200000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-200000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-200000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-200000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-200000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-175000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-205000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-205000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-205000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-205000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-205000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-205000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-180000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-210000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-210000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-210000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-210000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-210000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-210000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-185000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-215000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-215000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-215000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-215000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-215000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-215000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-190000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-220000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-220000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-220000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-220000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-220000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-220000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-195000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-225000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-225000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-225000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-225000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-225000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-225000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-200000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-230000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-230000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-230000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-230000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-230000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-230000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-205000] due to args.save_total_limit\n", "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n", "Saving model checkpoint to poem-gen-t5-small_v1/checkpoint-235000\n", "Configuration saved in poem-gen-t5-small_v1/checkpoint-235000/config.json\n", "Model weights saved in poem-gen-t5-small_v1/checkpoint-235000/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/checkpoint-235000/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/checkpoint-235000/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/checkpoint-235000/spiece.model\n", "Deleting older checkpoint [poem-gen-t5-small_v1/checkpoint-210000] due to args.save_total_limit\n", "\n", "\n", "Training completed. Do not forget to share your model on huggingface.co/models =)\n", "\n", "\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ "TrainOutput(global_step=237555, training_loss=2.936270662464186, metrics={'train_runtime': 19337.8395, 'train_samples_per_second': 49.138, 'train_steps_per_second': 12.284, 'total_flos': 1.5501099375919104e+16, 'train_loss': 2.936270662464186, 'epoch': 15.0})" ] }, "metadata": {}, "execution_count": 43 } ], "source": [ "trainer.train(resume_from_checkpoint=False)" ] }, { "cell_type": "markdown", "metadata": { "id": "GL4Ni8N1U9OR" }, "source": [ "## Check perplexity" ] }, { "cell_type": "code", "execution_count": 44, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 106 }, "id": "uq4PCfY7VA31", "outputId": "3fa98661-961d-4169-f16e-db1d842a2b14" }, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "***** Running Evaluation *****\n", " Num examples = 7038\n", " Batch size = 4\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "\n", "
\n", " \n", " \n", " [1760/1760 00:33]\n", "
\n", " " ] }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "Perplexity: 15.32\n" ] } ], "source": [ "eval_results = trainer.evaluate()\n", "print(f\"Perplexity: {math.exp(eval_results['eval_loss']):.2f}\")" ] }, { "cell_type": "markdown", "metadata": { "id": "jPL18rURVKTy" }, "source": [ "## Push to Hub" ] }, { "cell_type": "code", "execution_count": 45, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 576, "referenced_widgets": [ "e555ed0acf824700957724e9e31ead81", "49e14bcaa20a4ea6ab2d733d8112eb10", "bd53b49717d94821b547da31006cf348", "484e903da134402da4d7c21a9a84d11f", "a58c7a438cd44943975bca38e25776ae", "01500763d529467787e0d3b499e5b49d", "61e5d1ec94064c3b8582598e996b3f5a", "cec9f97b3f694ae9a1ca2589eb24f3e5", "31cbd9c5871c45f6a902f2df9592cf50", "468131b3e2204a01a1f0bdf9003c54ea", "e505e692daec45c89421ffab20f19eef", "bcbd7419037a424fb0a66cdeeea3d067", "b110a29ced1a43229d11ea6f70d58b4c", "1ff82a122e0746b991f7573b854296b9", "d18d9b2cebf2418fb83387536dcf9f91", "0a326fd4eb704585af9225bd81ef87ce", "cbdb54fcf12a4da794068a42f904d80a", "6c7121bbf72e4b3da438211c62c4cd81", "a962032b8aaf4d6c8dceca7f57850701", "8299566b317143a786ed6188c2e1f071", "088b54f8624b451caeea57610eba5407", "2ac1834ce6f84398bf690085d6dfabf6", "61ec4db037d14d7893a1cd1b69be6071", "f8b903230d044cd4a4a6285c4f8176c7", "baa0db69392a401da5d66f86d72a351b", "c80ca523165648b49a6727f160957ed5", "5ca4a02accc94894aba92afb0cc46c83", "9da7342a257343929039fe23f58c2571", "07f68a4342e44a2d9d7964f12d69883d", "10f5ba22cd024ebb8a480a56c444bbbb", "9d853fcd842040ddbd5ebae01f5d8ea1", "e49c244f62344042830aea9af335d1d6", "ea3f16e766ef41e3962d8a70bb4ad107" ] }, "id": "DqW57Mh2VIsH", "outputId": "be5d775a-5b75-43ec-e63f-e2a37b4a52e7" }, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "Saving model checkpoint to poem-gen-t5-small_v1\n", "Configuration saved in poem-gen-t5-small_v1/config.json\n", "Model weights saved in poem-gen-t5-small_v1/pytorch_model.bin\n", "tokenizer config file saved in poem-gen-t5-small_v1/tokenizer_config.json\n", "Special tokens file saved in poem-gen-t5-small_v1/special_tokens_map.json\n", "Copy vocab file to poem-gen-t5-small_v1/spiece.model\n", "Several commits (2) will be pushed upstream.\n", "The progress bars may be unreliable.\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "Upload file pytorch_model.bin: 0%| | 3.34k/231M [00:00 main\n", "\n", "Dropping the following result as it does not have all the necessary fields:\n", "{'task': {'name': 'Sequence-to-sequence Language Modeling', 'type': 'text2text-generation'}}\n", "remote: tput: No value for $TERM and no -T specified \n", "remote: tput: No value for $TERM and no -T specified \n", "remote: tput: No value for $TERM and no -T specified \n", "remote: tput: No value for $TERM and no -T specified \n", "To https://huggingface.co/DrishtiSharma/poem-gen-t5-small_v1\n", " 42c41b3..5d6100f main -> main\n", "\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ "'https://huggingface.co/DrishtiSharma/poem-gen-t5-small_v1/commit/42c41b39d13cd739a75fa71aad67ff1a56d601ba'" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "string" } }, "metadata": {}, "execution_count": 45 } ], "source": [ "trainer.push_to_hub()" ] }, { "cell_type": "markdown", "metadata": { "id": "YC_wJPR6at8g" }, "source": [ "# Test the model" ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "id": "GPDzswd9awJX", "colab": { "base_uri": "https://localhost:8080/", "height": 1000, "referenced_widgets": [ "cfc4401929e047feb67d836e172512d2", "dd05f427ee754b4c9289f1a37a07bcba", "9ecbb88190274d7080190eeb62cb152c", "0d2ecd0bb71140329b18083153ddac80", "ac0d25850b5044d8b695804fa16a3121", "8b1003d8d3bd43338457a0172a837472", "6534d9c49d2744ecb5e17069b5310494", "c2a7fd3935124e13bec01c7d5d3d2e1c", "cf88fe2e9f72496eaddcde4778140a08", "376411592ccd4102827d6d4cc8693025", "a015a7ada78b4897963d1ef4c088a31c", "b3403cfa359e4354be4ff7d1624716a9", "491c0b8fb2b0482faf6e3b265ee0324c", "a799d0ac37c5405c95db3d9ea533a763", "d470cf1ceffc43e8a990988e546ef91a", "04b2fdc35eab4ee9b7c41fbf2ffa8622", "c28f3124acfe42ac93d1f2179c74f880", "bc92cc62892545e4870b6928356c8aaa", "6701a79497f846118300293fd4e1cad6", "e241b8152419413b8e59df2557d1feb1", "9db0e7aec0e04d5e9129aaf4d8f877a3", "8c297cccf9144b22879dc64452b35cfc" ] }, "outputId": "a84a4d68-f2ee-4675-da04-ed3d8df59c16" }, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "https://huggingface.co/DrishtiSharma/poem-gen-t5-small_v1/resolve/main/config.json not found in cache or force_download set to True, downloading to /root/.cache/huggingface/transformers/tmpumxug7t6\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "Downloading: 0%| | 0.00/1.35k [00:00\"\"\"\n", "\n", "inputs = tokenizer(input_text, return_tensors=\"pt\")" ] }, { "cell_type": "code", "execution_count": 52, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "Oi51B7BXkI9u", "outputId": "46d93d45-8051-42f2-ba83-f3de45b9116d" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "y todos estaban despertando. Todos fueron al parque,\n", "y todos estaban despertar. Todos fueron al parque\n" ] } ], "source": [ "model_outputs = model_trained.generate(inputs[\"input_ids\"], max_length=100, num_beams=4, early_stopping=True,\n", " repetition_penalty=20.0, num_return_sequences=2)\n", "for output in model_outputs:\n", " print(tokenizer.decode(output, skip_special_tokens=True))" ] }, { "cell_type": "code", "execution_count": 53, "metadata": { "id": "hmnD8ioQbYHF" }, "outputs": [], "source": [ "def make_poem_v1(author, text, num_lines=5, avoid_repeated_outputs=True, repetition_penalty=10.0, num_beams=4):\n", " input_text = f\"\"\"poema: estilo: {author} && texto: {text} \"\"\"\n", " inputs = tokenizer(input_text, return_tensors=\"pt\")\n", " print(text)\n", "\n", " prev_output = ''\n", " for i in range(num_lines):\n", " outputs = model_trained.generate(inputs[\"input_ids\"], \n", " max_length=100, \n", " num_beams=num_beams, \n", " early_stopping=False,\n", " do_sample=True,\n", " temperature=.7,\n", " repetition_penalty=repetition_penalty, \n", " num_return_sequences=num_beams)\n", " detok_outputs = [tokenizer.decode(x, skip_special_tokens=True) for x in outputs]\n", " pre_output = detok_outputs[0]\n", " \n", " if avoid_repeated_outputs:\n", " # Choose an output different from the previous one\n", " for item in detok_outputs:\n", " # print(' ' + item)\n", " if item == prev_output:\n", " continue\n", " pre_output = item\n", "\n", " pre_output = pre_output.replace('.', ' ')\n", " print(pre_output)\n", " new_input = f\"\"\"poema: estilo: {author} && texto: {pre_output}\"\"\"\n", " inputs = tokenizer(new_input, return_tensors=\"pt\")\n", " prev_output = pre_output" ] }, { "cell_type": "code", "execution_count": 54, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "eVNzzqPAn7Du", "outputId": "eade996f-62d2-4204-f0a2-faae4fe391cb" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "la luz se prendió cuando la tarde cayó, la luna asomó su rostro y una estrella le sonrió\n", "y una sombra le dijo: «Quién me quedó!» Aqu se detiene\n", "aqu se detiene No me quedó,\n", "ni me quedó No,\n", "ni me quedó No,\n", "ni me quedó No, no puede\n" ] } ], "source": [ "make_poem_v1(author='leopoldo lugones',\n", " text='la luz se prendió cuando la tarde cayó, la luna asomó su rostro y una estrella le sonrió',\n", " num_lines=5,\n", " avoid_repeated_outputs=True,\n", " repetition_penalty=20.0, \n", " num_beams=4)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "UqUzT6KgZY_S" }, "outputs": [], "source": [ "" ] } ], "metadata": { "accelerator": "GPU", "colab": { "name": "hf_poem_generation_t5_v1.ipynb", "toc_visible": true, "provenance": [], "machine_shape": "hm" }, "kernelspec": { "display_name": "Python 3", "name": "python3" }, "language_info": { "name": "python" }, "widgets": { "application/vnd.jupyter.widget-state+json": { "a695d1e3bcdf4378bdcc69ba0712e261": { "model_module": "@jupyter-widgets/controls", "model_name": "HBoxModel", "model_module_version": 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