diff --git "a/novel-translation/06_tune-small-py3.11.ipynb" "b/novel-translation/06_tune-small-py3.11.ipynb" new file mode 100644--- /dev/null +++ "b/novel-translation/06_tune-small-py3.11.ipynb" @@ -0,0 +1,4673 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "0ea8b46b-839b-445b-8043-ccdf4e920ace", + "showTitle": false, + "title": "" + } + }, + "outputs": [], + "source": [ + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "6d394937-6c99-4a7c-9d32-7600a280032f", + "showTitle": false, + "title": "" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "workding dir: /home/inflaton/code/projects/courses/llm-finetuning\n" + ] + } + ], + "source": [ + "import os\n", + "import sys\n", + "from pathlib import Path\n", + "\n", + "workding_dir = str(Path.cwd().parent)\n", + "os.chdir(workding_dir)\n", + "sys.path.append(workding_dir)\n", + "print(\"workding dir:\", workding_dir)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "9f67ec60-2f24-411c-84eb-0dd664b44775", + "showTitle": false, + "title": "" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading env vars from: /home/inflaton/code/projects/courses/llm-finetuning/.env\n" + ] + }, + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from dotenv import find_dotenv, load_dotenv\n", + "\n", + "found_dotenv = find_dotenv(\".env\")\n", + "\n", + "if len(found_dotenv) == 0:\n", + " found_dotenv = find_dotenv(\".env.example\")\n", + "print(f\"loading env vars from: {found_dotenv}\")\n", + "load_dotenv(found_dotenv, override=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "application/vnd.databricks.v1+cell": { + "cellMetadata": {}, + "inputWidgets": {}, + "nuid": "f1597656-8042-4878-9d3b-9ebfb8dd86dc", + "showTitle": false, + "title": "" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "('unsloth/Qwen2-0.5B-Instruct-bnb-4bit',\n", + " True,\n", + " None,\n", + " None,\n", + " 2048,\n", + " 10,\n", + " None,\n", + " 'datasets/mac/mac.tsv',\n", + " 'results/mac-results_py3.11.csv')" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import os\n", + "\n", + "model_name = os.getenv(\"MODEL_NAME\")\n", + "token = os.getenv(\"HF_TOKEN\") or None\n", + "load_in_4bit = os.getenv(\"LOAD_IN_4BIT\") == \"true\"\n", + "local_model = os.getenv(\"LOCAL_MODEL\")\n", + "hub_model = os.getenv(\"HUB_MODEL\")\n", + "num_train_epochs = int(os.getenv(\"NUM_TRAIN_EPOCHS\") or 0)\n", + "data_path = os.getenv(\"DATA_PATH\")\n", + "results_path = os.getenv(\"RESULTS_PATH\")\n", + "\n", + "max_seq_length = 2048 # Choose any! We auto support RoPE Scaling internally!\n", + "dtype = (\n", + " None # None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+\n", + ")\n", + "\n", + "model_name, load_in_4bit, local_model, hub_model, max_seq_length, num_train_epochs, dtype, data_path, results_path" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Tue Jun 25 23:53:09 2024 \n", + "+---------------------------------------------------------------------------------------+\n", + "| NVIDIA-SMI 545.23.07 Driver Version: 546.12 CUDA Version: 12.3 |\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 NVIDIA GeForce RTX 4080 ... On | 00000000:01:00.0 On | N/A |\n", + "| N/A 54C P8 5W / 150W | 483MiB / 12282MiB | 9% 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": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Python 3.11.9\n", + "\u001b[33mWARNING: Package(s) not found: flash-attn\u001b[0m\u001b[33m\n", + "\u001b[0mCPU times: user 7.35 ms, sys: 1.47 ms, total: 8.81 ms\n", + "Wall time: 509 ms\n" + ] + } + ], + "source": [ + "%%time\n", + "!python --version\n", + "!pip show flash-attn" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Current Directory:\n", + "/home/inflaton/code/projects/courses/llm-finetuning\n", + "Tuning unsloth/Qwen2-0.5B-Instruct\n", + "loading env vars from: /home/inflaton/code/projects/courses/llm-finetuning/.env\n", + "Adding /home/inflaton/code/projects/courses/llm-finetuning to sys.path\n", + "πŸ¦₯ Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", + "[nltk_data] Downloading package wordnet to /home/inflaton/nltk_data...\n", + "[nltk_data] Package wordnet is already up-to-date!\n", + "[nltk_data] Downloading package punkt to /home/inflaton/nltk_data...\n", + "[nltk_data] Package punkt is already up-to-date!\n", + "[nltk_data] Downloading package omw-1.4 to /home/inflaton/nltk_data...\n", + "[nltk_data] Package omw-1.4 is already up-to-date!\n", + "loading /home/inflaton/code/projects/courses/llm-finetuning/llm_toolkit/translation_engine.py\n", + "unsloth/Qwen2-0.5B-Instruct True 2048 10 None datasets/mac/mac.tsv results/mac-results_py3.11.csv True True True\n", + "(1) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "0.0 GB of memory reserved.\n", + "loading model: unsloth/Qwen2-0.5B-Instruct\n", + "==((====))== Unsloth: Fast Qwen2 patching release 2024.6\n", + " \\\\ /| GPU: NVIDIA GeForce RTX 4080 Laptop GPU. Max memory: 11.994 GB. Platform = Linux.\n", + "O^O/ \\_/ \\ Pytorch: 2.3.0+cu121. CUDA = 8.9. CUDA Toolkit = 12.1.\n", + "\\ / Bfloat16 = TRUE. Xformers = 0.0.26.post1. FA = False.\n", + " \"-____-\" Free Apache license: http://github.com/unslothai/unsloth\n", + "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", + "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", + "(2) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "0.633 GB of memory reserved.\n", + "loading train/test data files\n", + "DatasetDict({\n", + " train: Dataset({\n", + " features: ['chinese', 'english', 'text', 'prompt'],\n", + " num_rows: 4528\n", + " })\n", + " test: Dataset({\n", + " features: ['chinese', 'english', 'text', 'prompt'],\n", + " num_rows: 1133\n", + " })\n", + "})\n", + "Evaluating base model: unsloth/Qwen2-0.5B-Instruct\n", + " 0%| | 0/1133 [00:00\n", + "--------\n", + "step 2: Oldθ€ΏδΈΎζžͺοΌŒζ–œη€ηœΌη›ηœ―θ΅·ζ₯οΌŒζ‰£εŠ¨ζ‰³ζœΊοΌŒη °ηš„δΈ€ε£°ε“οΌŒε­εΌΉδΈ€ι’—ι’—θ½εœ¨εœ°δΈŠοΌŒεƒζ˜―ζ‰“εœ¨ζ£‰θŠ±ε›’δΈŠδΈ€ζ ·οΌŒη °ηš„δΈ€ε£°εˆδΈ€ε£°οΌŒε£°ιŸ³εΎˆζΈ…θ„†γ€‚\n", + "--------\n", + "step 3: Oldθ€ΏδΈΎζžͺοΌŒζ–œη€ηœΌη›ηœ―θ΅·ζ₯οΌŒζ‰£εŠ¨ζ‰³ζœΊοΌŒη °ηš„δΈ€ε£°ε“οΌŒε­εΌΉδΈ€ι’—ι’—θ½εœ¨εœ°δΈŠοΌŒεƒζ˜―ζ‰“εœ¨ζ£‰θŠ±ε›’δΈŠδΈ€ζ ·οΌŒη °ηš„δΈ€ε£°εˆδΈ€ε£°οΌŒε£°ιŸ³εΎˆζΈ…θ„†γ€‚\n", + "100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1133/1133 [21:27<00:00, 1.14s/it]\n", + " chinese ... unsloth/Qwen2-0.5B-Instruct\n", + "0 老耿端衷ζžͺοΌŒηœ―ηΌθ΅·δΈ€εͺδΈ‰θ§’ηœΌοΌŒδΈ€ζ‚ζ‰³ζœΊε“δΊ†ζžͺοΌŒε†°ι›Ήθˆ¬ηš„ι‡‘ιΊ»ι›€εŠˆε“©ε•ͺε•¦εΎ€δΈ‹θ½οΌŒι“η ‚ε­εœ¨ζŸ³ζžι—΄ι£ž... ... Oldθ€ΏδΈΎζžͺοΌŒζ–œη€ηœΌη›ηœ―θ΅·ζ₯οΌŒζ‰£εŠ¨ζ‰³ζœΊοΌŒη °ηš„δΈ€ε£°ε“οΌŒε­εΌΉδΈ€ι’—ι’—θ½εœ¨εœ°δΈŠοΌŒεƒζ˜―ζ‰“εœ¨ζ£‰θŠ±ε›’δΈŠδΈ€ζ ·...\n", + "\n", + "[1 rows x 3 columns]\n", + "(3) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "0.893 GB of memory reserved.\n", + "Unsloth 2024.6 patched 24 layers with 0 QKV layers, 24 O layers and 24 MLP layers.\n", + "/home/inflaton/miniconda3/envs/llm-fine-tune/lib/python3.11/site-packages/transformers/training_args.py:1965: FutureWarning: `--push_to_hub_token` is deprecated and will be removed in version 5 of πŸ€— Transformers. Use `--hub_token` instead.\n", + " warnings.warn(\n", + "/home/inflaton/miniconda3/envs/llm-fine-tune/lib/python3.11/site-packages/trl/trainer/sft_trainer.py:269: UserWarning: You passed a `max_seq_length` argument to the SFTTrainer, the value you passed will override the one in the `SFTConfig`.\n", + " warnings.warn(\n", + "/home/inflaton/miniconda3/envs/llm-fine-tune/lib/python3.11/site-packages/trl/trainer/sft_trainer.py:283: UserWarning: You passed a `dataset_num_proc` argument to the SFTTrainer, the value you passed will override the one in the `SFTConfig`.\n", + " warnings.warn(\n", + "/home/inflaton/miniconda3/envs/llm-fine-tune/lib/python3.11/site-packages/trl/trainer/sft_trainer.py:307: UserWarning: You passed a `dataset_text_field` argument to the SFTTrainer, the value you passed will override the one in the `SFTConfig`.\n", + " warnings.warn(\n", + "Map (num_proc=2): 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 4528/4528 [00:00<00:00, 5300.69 examples/s]\n", + "(4) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "0.893 GB of memory reserved.\n", + "==((====))== Unsloth - 2x faster free finetuning | Num GPUs = 1\n", + " \\\\ /| Num examples = 4,528 | Num Epochs = 10\n", + "O^O/ \\_/ \\ Batch size per device = 2 | Gradient Accumulation steps = 4\n", + "\\ / Total batch size = 8 | Total steps = 5,660\n", + " \"-____-\" Number of trainable parameters = 8,798,208\n", + "{'loss': 1.9402, 'grad_norm': 0.9608356952667236, 'learning_rate': 0.00019664014146772768, 'epoch': 0.18}\n", + "{'loss': 1.7757, 'grad_norm': 0.8031952977180481, 'learning_rate': 0.0001931034482758621, 'epoch': 0.35}\n", + "{'loss': 1.7142, 'grad_norm': 0.9293338656425476, 'learning_rate': 0.00018956675508399648, 'epoch': 0.53}\n", + "{'loss': 1.7148, 'grad_norm': 0.7500923275947571, 'learning_rate': 0.00018603006189213086, 'epoch': 0.71}\n", + "{'loss': 1.6853, 'grad_norm': 0.8244311809539795, 'learning_rate': 0.00018249336870026527, 'epoch': 0.88}\n", + "{'loss': 1.607, 'grad_norm': 0.7938973903656006, 'learning_rate': 0.00017895667550839965, 'epoch': 1.06}\n", + "{'loss': 1.491, 'grad_norm': 0.8929483890533447, 'learning_rate': 0.00017541998231653406, 'epoch': 1.24}\n", + "{'loss': 1.5396, 'grad_norm': 0.9767352342605591, 'learning_rate': 0.00017188328912466844, 'epoch': 1.41}\n", + "{'loss': 1.4711, 'grad_norm': 1.0663349628448486, 'learning_rate': 0.00016834659593280285, 'epoch': 1.59}\n", + "{'loss': 1.4675, 'grad_norm': 0.9794139862060547, 'learning_rate': 0.00016480990274093723, 'epoch': 1.77}\n", + "{'loss': 1.5265, 'grad_norm': 1.0100280046463013, 'learning_rate': 0.00016127320954907164, 'epoch': 1.94}\n", + "{'loss': 1.3482, 'grad_norm': 1.1571651697158813, 'learning_rate': 0.000157736516357206, 'epoch': 2.12}\n", + "{'loss': 1.2146, 'grad_norm': 1.173205018043518, 'learning_rate': 0.0001541998231653404, 'epoch': 2.3}\n", + "{'loss': 1.2565, 'grad_norm': 1.2972688674926758, 'learning_rate': 0.0001506631299734748, 'epoch': 2.47}\n", + "{'loss': 1.2542, 'grad_norm': 1.3474286794662476, 'learning_rate': 0.0001471264367816092, 'epoch': 2.65}\n", + "{'loss': 1.2652, 'grad_norm': 1.1654258966445923, 'learning_rate': 0.0001435897435897436, 'epoch': 2.83}\n", + "{'loss': 1.2327, 'grad_norm': 1.0851577520370483, 'learning_rate': 0.000140053050397878, 'epoch': 3.0}\n", + "{'loss': 0.9784, 'grad_norm': 1.477825403213501, 'learning_rate': 0.0001365163572060124, 'epoch': 3.18}\n", + "{'loss': 0.9903, 'grad_norm': 1.5403794050216675, 'learning_rate': 0.00013297966401414678, 'epoch': 3.36}\n", + "{'loss': 0.9977, 'grad_norm': 1.510469913482666, 'learning_rate': 0.0001294429708222812, 'epoch': 3.53}\n", + "{'loss': 0.9786, 'grad_norm': 1.5427402257919312, 'learning_rate': 0.00012590627763041555, 'epoch': 3.71}\n", + "{'loss': 1.0211, 'grad_norm': 1.569674015045166, 'learning_rate': 0.00012236958443854996, 'epoch': 3.89}\n", + "{'loss': 0.9282, 'grad_norm': 1.5466079711914062, 'learning_rate': 0.00011883289124668435, 'epoch': 4.06}\n", + "{'loss': 0.7374, 'grad_norm': 1.6999439001083374, 'learning_rate': 0.00011529619805481875, 'epoch': 4.24}\n", + "{'loss': 0.7371, 'grad_norm': 1.7169603109359741, 'learning_rate': 0.00011175950486295315, 'epoch': 4.42}\n", + "{'loss': 0.7729, 'grad_norm': 2.1618764400482178, 'learning_rate': 0.00010822281167108754, 'epoch': 4.59}\n", + "{'loss': 0.7718, 'grad_norm': 2.412935972213745, 'learning_rate': 0.00010468611847922194, 'epoch': 4.77}\n", + "{'loss': 0.7913, 'grad_norm': 1.8272628784179688, 'learning_rate': 0.00010114942528735633, 'epoch': 4.95}\n", + "{'loss': 0.6267, 'grad_norm': 1.8343967199325562, 'learning_rate': 9.761273209549072e-05, 'epoch': 5.12}\n", + "{'loss': 0.5543, 'grad_norm': 1.6036676168441772, 'learning_rate': 9.407603890362513e-05, 'epoch': 5.3}\n", + "{'loss': 0.5589, 'grad_norm': 1.6545743942260742, 'learning_rate': 9.053934571175951e-05, 'epoch': 5.48}\n", + "{'loss': 0.5872, 'grad_norm': 1.8736636638641357, 'learning_rate': 8.70026525198939e-05, 'epoch': 5.65}\n", + "{'loss': 0.5794, 'grad_norm': 2.7655928134918213, 'learning_rate': 8.34659593280283e-05, 'epoch': 5.83}\n", + "{'loss': 0.5763, 'grad_norm': 2.0712125301361084, 'learning_rate': 7.99292661361627e-05, 'epoch': 6.01}\n", + "{'loss': 0.3967, 'grad_norm': 1.8133138418197632, 'learning_rate': 7.639257294429708e-05, 'epoch': 6.18}\n", + "{'loss': 0.4092, 'grad_norm': 1.7030404806137085, 'learning_rate': 7.285587975243147e-05, 'epoch': 6.36}\n", + "{'loss': 0.4278, 'grad_norm': 2.3163561820983887, 'learning_rate': 6.931918656056587e-05, 'epoch': 6.54}\n", + "{'loss': 0.4194, 'grad_norm': 1.8104350566864014, 'learning_rate': 6.578249336870027e-05, 'epoch': 6.71}\n", + "{'loss': 0.4248, 'grad_norm': 1.6338876485824585, 'learning_rate': 6.224580017683466e-05, 'epoch': 6.89}\n", + "{'loss': 0.3832, 'grad_norm': 1.7445095777511597, 'learning_rate': 5.870910698496905e-05, 'epoch': 7.07}\n", + "{'loss': 0.2912, 'grad_norm': 1.7364373207092285, 'learning_rate': 5.517241379310345e-05, 'epoch': 7.24}\n", + "{'loss': 0.3119, 'grad_norm': 1.3449686765670776, 'learning_rate': 5.163572060123785e-05, 'epoch': 7.42}\n", + "{'loss': 0.3127, 'grad_norm': 1.8036069869995117, 'learning_rate': 4.809902740937224e-05, 'epoch': 7.6}\n", + "{'loss': 0.3028, 'grad_norm': 2.0399818420410156, 'learning_rate': 4.4562334217506634e-05, 'epoch': 7.77}\n", + "{'loss': 0.318, 'grad_norm': 1.544445514678955, 'learning_rate': 4.1025641025641023e-05, 'epoch': 7.95}\n", + "{'loss': 0.2465, 'grad_norm': 1.361892819404602, 'learning_rate': 3.7488947833775426e-05, 'epoch': 8.13}\n", + "{'loss': 0.2259, 'grad_norm': 2.45100736618042, 'learning_rate': 3.3952254641909815e-05, 'epoch': 8.3}\n", + "{'loss': 0.2285, 'grad_norm': 1.014116883277893, 'learning_rate': 3.041556145004421e-05, 'epoch': 8.48}\n", + "{'loss': 0.2358, 'grad_norm': 1.2610195875167847, 'learning_rate': 2.6878868258178604e-05, 'epoch': 8.66}\n", + "{'loss': 0.2351, 'grad_norm': 1.6966944932937622, 'learning_rate': 2.3342175066313e-05, 'epoch': 8.83}\n", + "{'loss': 0.2387, 'grad_norm': 1.0741287469863892, 'learning_rate': 1.9805481874447392e-05, 'epoch': 9.01}\n", + "{'loss': 0.1809, 'grad_norm': 1.14618980884552, 'learning_rate': 1.6268788682581788e-05, 'epoch': 9.19}\n", + "{'loss': 0.1911, 'grad_norm': 1.1346627473831177, 'learning_rate': 1.273209549071618e-05, 'epoch': 9.36}\n", + "{'loss': 0.1869, 'grad_norm': 1.1694375276565552, 'learning_rate': 9.195402298850575e-06, 'epoch': 9.54}\n", + "{'loss': 0.1878, 'grad_norm': 1.8589993715286255, 'learning_rate': 5.658709106984969e-06, 'epoch': 9.72}\n", + "{'loss': 0.1889, 'grad_norm': 0.9836981892585754, 'learning_rate': 2.1220159151193635e-06, 'epoch': 9.89}\n", + "{'train_runtime': 4526.9366, 'train_samples_per_second': 10.002, 'train_steps_per_second': 1.25, 'train_loss': 0.7976709857846317, 'epoch': 10.0}\n", + "100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 5660/5660 [1:15:26<00:00, 1.25it/s]\n", + "(5) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "4526.9366 seconds used for training.\n", + "75.45 minutes used for training.\n", + "Peak reserved memory = 1.371 GB.\n", + "Peak reserved memory for training = 0.478 GB.\n", + "Peak reserved memory % of max memory = 11.431 %.\n", + "Peak reserved memory for training % of max memory = 3.985 %.\n", + "Evaluating fine-tuned model: unsloth/Qwen2-0.5B-Instruct\n", + " 0%| | 0/1133 [00:00\n", + "--------\n", + "step 2: Old Geng raised his rifle and tilted his head to one side; as the shotgun blast issued, crinkles formed in his eye, and ice-shells splattered through the air like hailstones.\n", + "--------\n", + "step 3: Old Geng raised his rifle and tilted his head to one side; as the shotgun blast issued, crinkles formed in his eye, and ice-shells splattered through the air like hailstones.\n", + "100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1133/1133 [29:54<00:00, 1.58s/it]\n", + " chinese ... unsloth/Qwen2-0.5B-Instruct(finetuned)\n", + "0 老耿端衷ζžͺοΌŒηœ―ηΌθ΅·δΈ€εͺδΈ‰θ§’ηœΌοΌŒδΈ€ζ‚ζ‰³ζœΊε“δΊ†ζžͺοΌŒε†°ι›Ήθˆ¬ηš„ι‡‘ιΊ»ι›€εŠˆε“©ε•ͺε•¦εΎ€δΈ‹θ½οΌŒι“η ‚ε­εœ¨ζŸ³ζžι—΄ι£ž... ... Old Geng raised his rifle and tilted his head ...\n", + "\n", + "[1 rows x 4 columns]\n", + "(6) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "1.371 GB of memory reserved.\n", + "model.safetensors: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 493M/493M [00:50<00:00, 9.77MB/s]\n", + "Saved model to https://huggingface.co/Qwen2-0.5B-Instruct-MAC-lora\n", + "README.md: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 599/599 [00:00<00:00, 11.4MB/s]\n", + "Unsloth: Saving tokenizer... Done.\n", + "Unsloth: Saving model... Done.\n", + "Unsloth: Saving LoRA adapters. Please wait...\n", + "401 Client Error: Unauthorized for url: https://huggingface.co/api/repos/create (Request ID: Root=1-667b060d-6b558b430a940ed15545a0b3;57af47e9-c736-4f24-80b8-1d4983acc0e0)\n", + "\n", + "Invalid username or password.\n", + "Tuning unsloth/Qwen2-1.5B-Instruct\n", + "loading env vars from: /home/inflaton/code/projects/courses/llm-finetuning/.env\n", + "Adding /home/inflaton/code/projects/courses/llm-finetuning to sys.path\n", + "πŸ¦₯ Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", + "[nltk_data] Downloading package wordnet to /home/inflaton/nltk_data...\n", + "[nltk_data] Package wordnet is already up-to-date!\n", + "[nltk_data] Downloading package punkt to /home/inflaton/nltk_data...\n", + "[nltk_data] Package punkt is already up-to-date!\n", + "[nltk_data] Downloading package omw-1.4 to /home/inflaton/nltk_data...\n", + "[nltk_data] Package omw-1.4 is already up-to-date!\n", + "loading /home/inflaton/code/projects/courses/llm-finetuning/llm_toolkit/translation_engine.py\n", + "unsloth/Qwen2-1.5B-Instruct True 2048 10 None datasets/mac/mac.tsv results/mac-results_py3.11.csv True True True\n", + "(1) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "0.0 GB of memory reserved.\n", + "loading model: unsloth/Qwen2-1.5B-Instruct\n", + "==((====))== Unsloth: Fast Qwen2 patching release 2024.6\n", + " \\\\ /| GPU: NVIDIA GeForce RTX 4080 Laptop GPU. Max memory: 11.994 GB. Platform = Linux.\n", + "O^O/ \\_/ \\ Pytorch: 2.3.0+cu121. CUDA = 8.9. CUDA Toolkit = 12.1.\n", + "\\ / Bfloat16 = TRUE. Xformers = 0.0.26.post1. FA = False.\n", + " \"-____-\" Free Apache license: http://github.com/unslothai/unsloth\n", + "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", + "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", + "(2) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "1.516 GB of memory reserved.\n", + "loading train/test data files\n", + "Map: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 4528/4528 [00:00<00:00, 31812.02 examples/s]\n", + "Map: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1133/1133 [00:00<00:00, 14717.68 examples/s]\n", + "DatasetDict({\n", + " train: Dataset({\n", + " features: ['chinese', 'english', 'text', 'prompt'],\n", + " num_rows: 4528\n", + " })\n", + " test: Dataset({\n", + " features: ['chinese', 'english', 'text', 'prompt'],\n", + " num_rows: 1133\n", + " })\n", + "})\n", + "Evaluating base model: unsloth/Qwen2-1.5B-Instruct\n", + " 0%| | 0/1133 [00:00\n", + "--------\n", + "step 2: Lao Jing lifted up his gun, squinted one of his two triangular eyes, and fired a shot with his gun. A hail of golden sparrows rained down from above, striking the willow branches with a loud clatter, making a sound.\n", + "--------\n", + "step 3: Lao Jing lifted up his gun, squinted one of his two triangular eyes, and fired a shot with his gun. A hail of golden sparrows rained down from above, striking the willow branches with a loud clatter, making a sound.\n", + "100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1133/1133 [1:34:06<00:00, 4.98s/it]\n", + " chinese ... unsloth/Qwen2-1.5B-Instruct\n", + "0 老耿端衷ζžͺοΌŒηœ―ηΌθ΅·δΈ€εͺδΈ‰θ§’ηœΌοΌŒδΈ€ζ‚ζ‰³ζœΊε“δΊ†ζžͺοΌŒε†°ι›Ήθˆ¬ηš„ι‡‘ιΊ»ι›€εŠˆε“©ε•ͺε•¦εΎ€δΈ‹θ½οΌŒι“η ‚ε­εœ¨ζŸ³ζžι—΄ι£ž... ... Lao Jing lifted up his gun, squinted one of hi...\n", + "\n", + "[1 rows x 5 columns]\n", + "(3) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "3.945 GB of memory reserved.\n", + "Unsloth 2024.6 patched 28 layers with 0 QKV layers, 28 O layers and 28 MLP layers.\n", + "/home/inflaton/miniconda3/envs/llm-fine-tune/lib/python3.11/site-packages/transformers/training_args.py:1965: FutureWarning: `--push_to_hub_token` is deprecated and will be removed in version 5 of πŸ€— Transformers. Use `--hub_token` instead.\n", + " warnings.warn(\n", + "/home/inflaton/miniconda3/envs/llm-fine-tune/lib/python3.11/site-packages/trl/trainer/sft_trainer.py:269: UserWarning: You passed a `max_seq_length` argument to the SFTTrainer, the value you passed will override the one in the `SFTConfig`.\n", + " warnings.warn(\n", + "/home/inflaton/miniconda3/envs/llm-fine-tune/lib/python3.11/site-packages/trl/trainer/sft_trainer.py:283: UserWarning: You passed a `dataset_num_proc` argument to the SFTTrainer, the value you passed will override the one in the `SFTConfig`.\n", + " warnings.warn(\n", + "/home/inflaton/miniconda3/envs/llm-fine-tune/lib/python3.11/site-packages/trl/trainer/sft_trainer.py:307: UserWarning: You passed a `dataset_text_field` argument to the SFTTrainer, the value you passed will override the one in the `SFTConfig`.\n", + " warnings.warn(\n", + "Map (num_proc=2): 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 4528/4528 [00:02<00:00, 2177.21 examples/s]\n", + "(4) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "3.945 GB of memory reserved.\n", + "==((====))== Unsloth - 2x faster free finetuning | Num GPUs = 1\n", + " \\\\ /| Num examples = 4,528 | Num Epochs = 10\n", + "O^O/ \\_/ \\ Batch size per device = 2 | Gradient Accumulation steps = 4\n", + "\\ / Total batch size = 8 | Total steps = 5,660\n", + " \"-____-\" Number of trainable parameters = 18,464,768\n", + "{'loss': 1.7414, 'grad_norm': 0.645324170589447, 'learning_rate': 0.00019664014146772768, 'epoch': 0.18}\n", + "{'loss': 1.5681, 'grad_norm': 0.6221398115158081, 'learning_rate': 0.0001931034482758621, 'epoch': 0.35}\n", + "{'loss': 1.5156, 'grad_norm': 0.6400603652000427, 'learning_rate': 0.00018956675508399648, 'epoch': 0.53}\n", + "{'loss': 1.5174, 'grad_norm': 0.5692432522773743, 'learning_rate': 0.00018603006189213086, 'epoch': 0.71}\n", + "{'loss': 1.496, 'grad_norm': 0.5720127820968628, 'learning_rate': 0.00018249336870026527, 'epoch': 0.88}\n", + "{'loss': 1.4181, 'grad_norm': 0.5995662808418274, 'learning_rate': 0.00017895667550839965, 'epoch': 1.06}\n", + "{'loss': 1.2976, 'grad_norm': 0.7103854417800903, 'learning_rate': 0.00017541998231653406, 'epoch': 1.24}\n", + "{'loss': 1.3392, 'grad_norm': 0.6867524981498718, 'learning_rate': 0.00017188328912466844, 'epoch': 1.41}\n", + "{'loss': 1.2788, 'grad_norm': 0.8870283961296082, 'learning_rate': 0.00016834659593280285, 'epoch': 1.59}\n", + "{'loss': 1.2799, 'grad_norm': 0.8677213788032532, 'learning_rate': 0.00016480990274093723, 'epoch': 1.77}\n", + "{'loss': 1.3311, 'grad_norm': 0.824891984462738, 'learning_rate': 0.00016127320954907164, 'epoch': 1.94}\n", + "{'loss': 1.1283, 'grad_norm': 0.9994134902954102, 'learning_rate': 0.000157736516357206, 'epoch': 2.12}\n", + "{'loss': 0.9958, 'grad_norm': 1.1032615900039673, 'learning_rate': 0.0001541998231653404, 'epoch': 2.3}\n", + "{'loss': 1.0305, 'grad_norm': 1.2964789867401123, 'learning_rate': 0.0001506631299734748, 'epoch': 2.47}\n", + "{'loss': 1.0345, 'grad_norm': 1.1391383409500122, 'learning_rate': 0.0001471264367816092, 'epoch': 2.65}\n", + "{'loss': 1.0352, 'grad_norm': 1.033879041671753, 'learning_rate': 0.0001435897435897436, 'epoch': 2.83}\n", + "{'loss': 1.0078, 'grad_norm': 0.893123209476471, 'learning_rate': 0.000140053050397878, 'epoch': 3.0}\n", + "{'loss': 0.6974, 'grad_norm': 1.3191255331039429, 'learning_rate': 0.0001365163572060124, 'epoch': 3.18}\n", + "{'loss': 0.7094, 'grad_norm': 1.3912413120269775, 'learning_rate': 0.00013297966401414678, 'epoch': 3.36}\n", + "{'loss': 0.7159, 'grad_norm': 1.262569785118103, 'learning_rate': 0.0001294429708222812, 'epoch': 3.53}\n", + "{'loss': 0.7052, 'grad_norm': 1.4299038648605347, 'learning_rate': 0.00012590627763041555, 'epoch': 3.71}\n", + "{'loss': 0.7441, 'grad_norm': 1.2525451183319092, 'learning_rate': 0.00012236958443854996, 'epoch': 3.89}\n", + "{'loss': 0.6426, 'grad_norm': 1.1614264249801636, 'learning_rate': 0.00011883289124668435, 'epoch': 4.06}\n", + "{'loss': 0.4613, 'grad_norm': 1.4634888172149658, 'learning_rate': 0.00011529619805481875, 'epoch': 4.24}\n", + "{'loss': 0.4463, 'grad_norm': 1.479321002960205, 'learning_rate': 0.00011175950486295315, 'epoch': 4.42}\n", + "{'loss': 0.4803, 'grad_norm': 1.524327278137207, 'learning_rate': 0.00010822281167108754, 'epoch': 4.59}\n", + "{'loss': 0.4775, 'grad_norm': 1.8287591934204102, 'learning_rate': 0.00010468611847922194, 'epoch': 4.77}\n", + "{'loss': 0.4858, 'grad_norm': 1.5343736410140991, 'learning_rate': 0.00010114942528735633, 'epoch': 4.95}\n", + "{'loss': 0.3607, 'grad_norm': 1.509474277496338, 'learning_rate': 9.761273209549072e-05, 'epoch': 5.12}\n", + "{'loss': 0.291, 'grad_norm': 0.9709746837615967, 'learning_rate': 9.407603890362513e-05, 'epoch': 5.3}\n", + "{'loss': 0.297, 'grad_norm': 1.1549153327941895, 'learning_rate': 9.053934571175951e-05, 'epoch': 5.48}\n", + "{'loss': 0.3137, 'grad_norm': 1.5136038064956665, 'learning_rate': 8.70026525198939e-05, 'epoch': 5.65}\n", + "{'loss': 0.3086, 'grad_norm': 1.5126714706420898, 'learning_rate': 8.34659593280283e-05, 'epoch': 5.83}\n", + "{'loss': 0.3054, 'grad_norm': 1.2357054948806763, 'learning_rate': 7.99292661361627e-05, 'epoch': 6.01}\n", + "{'loss': 0.1908, 'grad_norm': 0.998966634273529, 'learning_rate': 7.639257294429708e-05, 'epoch': 6.18}\n", + "{'loss': 0.2016, 'grad_norm': 1.4552719593048096, 'learning_rate': 7.285587975243147e-05, 'epoch': 6.36}\n", + "{'loss': 0.2063, 'grad_norm': 1.193115234375, 'learning_rate': 6.931918656056587e-05, 'epoch': 6.54}\n", + "{'loss': 0.2068, 'grad_norm': 1.1482857465744019, 'learning_rate': 6.578249336870027e-05, 'epoch': 6.71}\n", + "{'loss': 0.2145, 'grad_norm': 1.2252038717269897, 'learning_rate': 6.224580017683466e-05, 'epoch': 6.89}\n", + "{'loss': 0.194, 'grad_norm': 0.8770560026168823, 'learning_rate': 5.870910698496905e-05, 'epoch': 7.07}\n", + "{'loss': 0.1487, 'grad_norm': 0.7064879536628723, 'learning_rate': 5.517241379310345e-05, 'epoch': 7.24}\n", + "{'loss': 0.1571, 'grad_norm': 0.8916934132575989, 'learning_rate': 5.163572060123785e-05, 'epoch': 7.42}\n", + "{'loss': 0.1576, 'grad_norm': 0.910902738571167, 'learning_rate': 4.809902740937224e-05, 'epoch': 7.6}\n", + "{'loss': 0.1576, 'grad_norm': 1.3216708898544312, 'learning_rate': 4.4562334217506634e-05, 'epoch': 7.77}\n", + "{'loss': 0.1596, 'grad_norm': 0.9173678755760193, 'learning_rate': 4.1025641025641023e-05, 'epoch': 7.95}\n", + "{'loss': 0.1368, 'grad_norm': 0.7557782530784607, 'learning_rate': 3.7488947833775426e-05, 'epoch': 8.13}\n", + "{'loss': 0.1305, 'grad_norm': 1.3723442554473877, 'learning_rate': 3.3952254641909815e-05, 'epoch': 8.3}\n", + "{'loss': 0.1315, 'grad_norm': 0.4736746847629547, 'learning_rate': 3.041556145004421e-05, 'epoch': 8.48}\n", + "{'loss': 0.1328, 'grad_norm': 0.4113923907279968, 'learning_rate': 2.6878868258178604e-05, 'epoch': 8.66}\n", + "{'loss': 0.1343, 'grad_norm': 0.628764271736145, 'learning_rate': 2.3342175066313e-05, 'epoch': 8.83}\n", + "{'loss': 0.1329, 'grad_norm': 0.5089218020439148, 'learning_rate': 1.9805481874447392e-05, 'epoch': 9.01}\n", + "{'loss': 0.1179, 'grad_norm': 0.45263954997062683, 'learning_rate': 1.6268788682581788e-05, 'epoch': 9.19}\n", + "{'loss': 0.1185, 'grad_norm': 0.552614152431488, 'learning_rate': 1.273209549071618e-05, 'epoch': 9.36}\n", + "{'loss': 0.1193, 'grad_norm': 0.46947821974754333, 'learning_rate': 9.195402298850575e-06, 'epoch': 9.54}\n", + "{'loss': 0.1202, 'grad_norm': 0.5204765200614929, 'learning_rate': 5.658709106984969e-06, 'epoch': 9.72}\n", + "{'loss': 0.1232, 'grad_norm': 0.4254581928253174, 'learning_rate': 2.1220159151193635e-06, 'epoch': 9.89}\n", + "{'train_runtime': 16066.3343, 'train_samples_per_second': 2.818, 'train_steps_per_second': 0.352, 'train_loss': 0.5993303972082509, 'epoch': 10.0}\n", + "100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 5660/5660 [4:27:46<00:00, 2.84s/it]\n", + "(5) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "16066.3343 seconds used for training.\n", + "267.77 minutes used for training.\n", + "Peak reserved memory = 3.945 GB.\n", + "Peak reserved memory for training = 0.0 GB.\n", + "Peak reserved memory % of max memory = 32.891 %.\n", + "Peak reserved memory for training % of max memory = 0.0 %.\n", + "Evaluating fine-tuned model: unsloth/Qwen2-1.5B-Instruct\n", + " 0%| | 0/1133 [00:00\n", + "--------\n", + "step 2: Old Geng raised the pistol to his eye, squeezed the trigger, and rainafterdowned birds landed: Golden sparrows, dead or alive, screeched and dropped from the treetops, sending sticks flying everywhere.\n", + "--------\n", + "step 3: Old Geng raised the pistol to his eye, squeezed the trigger, and rainafterdowned birds landed: Golden sparrows, dead or alive, screeched and dropped from the treetops, sending sticks flying everywhere.\n", + "100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1133/1133 [2:11:15<00:00, 6.95s/it]\n", + " chinese ... unsloth/Qwen2-1.5B-Instruct(finetuned)\n", + "0 老耿端衷ζžͺοΌŒηœ―ηΌθ΅·δΈ€εͺδΈ‰θ§’ηœΌοΌŒδΈ€ζ‚ζ‰³ζœΊε“δΊ†ζžͺοΌŒε†°ι›Ήθˆ¬ηš„ι‡‘ιΊ»ι›€εŠˆε“©ε•ͺε•¦εΎ€δΈ‹θ½οΌŒι“η ‚ε­εœ¨ζŸ³ζžι—΄ι£ž... ... Old Geng raised the pistol to his eye, squeeze...\n", + "\n", + "[1 rows x 6 columns]\n", + "(6) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "5.33 GB of memory reserved.\n", + "model.safetensors: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1.22G/1.22G [01:25<00:00, 14.3MB/s]\n", + "Saved model to https://huggingface.co/Qwen2-1.5B-Instruct-MAC-lora\n", + "README.md: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 599/599 [00:00<00:00, 3.80MB/s]\n", + "Unsloth: Saving tokenizer... Done.\n", + "Unsloth: Saving model... Done.\n", + "Unsloth: Saving LoRA adapters. Please wait...\n", + "401 Client Error: Unauthorized for url: https://huggingface.co/api/repos/create (Request ID: Root=1-667b7a4d-4dd9df470d5a01b733cc9060;fa501a9a-6bbd-4865-bbdc-ddcc5f272821)\n", + "\n", + "Invalid username or password.\n", + "CPU times: user 13min 32s, sys: 5min 37s, total: 19min 10s\n", + "Wall time: 10h 24min 39s\n" + ] + } + ], + "source": [ + "%%time\n", + "\n", + "!./scripts/tune-small-2.sh" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Current Directory:\n", + "/home/inflaton/code/projects/courses/llm-finetuning\n", + "Tuning unsloth/Qwen2-0.5B-Instruct-bnb-4bit\n", + "loading env vars from: /home/inflaton/code/projects/courses/llm-finetuning/.env\n", + "Adding /home/inflaton/code/projects/courses/llm-finetuning to sys.path\n", + "πŸ¦₯ Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", + "[nltk_data] Downloading package wordnet to /home/inflaton/nltk_data...\n", + "[nltk_data] Package wordnet is already up-to-date!\n", + "[nltk_data] Downloading package punkt to /home/inflaton/nltk_data...\n", + "[nltk_data] Package punkt is already up-to-date!\n", + "[nltk_data] Downloading package omw-1.4 to /home/inflaton/nltk_data...\n", + "[nltk_data] Package omw-1.4 is already up-to-date!\n", + "loading /home/inflaton/code/projects/courses/llm-finetuning/llm_toolkit/translation_engine.py\n", + "unsloth/Qwen2-0.5B-Instruct-bnb-4bit True 2048 10 None datasets/mac/mac.tsv results/mac-results_py3.11.csv True True True\n", + "(1) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "0.0 GB of memory reserved.\n", + "loading model: unsloth/Qwen2-0.5B-Instruct-bnb-4bit\n", + "==((====))== Unsloth: Fast Qwen2 patching release 2024.6\n", + " \\\\ /| GPU: NVIDIA GeForce RTX 4080 Laptop GPU. Max memory: 11.994 GB. Platform = Linux.\n", + "O^O/ \\_/ \\ Pytorch: 2.3.0+cu121. CUDA = 8.9. CUDA Toolkit = 12.1.\n", + "\\ / Bfloat16 = TRUE. Xformers = 0.0.26.post1. FA = False.\n", + " \"-____-\" Free Apache license: http://github.com/unslothai/unsloth\n", + "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", + "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", + "(2) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "0.633 GB of memory reserved.\n", + "loading train/test data files\n", + "Map: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 4528/4528 [00:00<00:00, 12373.02 examples/s]\n", + "Map: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1133/1133 [00:00<00:00, 9100.92 examples/s]\n", + "DatasetDict({\n", + " train: Dataset({\n", + " features: ['chinese', 'english', 'text', 'prompt'],\n", + " num_rows: 4528\n", + " })\n", + " test: Dataset({\n", + " features: ['chinese', 'english', 'text', 'prompt'],\n", + " num_rows: 1133\n", + " })\n", + "})\n", + "Evaluating base model: unsloth/Qwen2-0.5B-Instruct-bnb-4bit\n", + " 0%| | 0/1133 [00:00\n", + "--------\n", + "step 2: Old Tang raises his gun, half-closed eyes, firing the trigger of the revolver. The bullet crackles as the hammer rings, a thunderous bang that echoes through the branches of the tree. The sand grains hit the ground with a thud, echoing like a drum.\n", + "--------\n", + "step 3: Old Tang raises his gun, half-closed eyes, firing the trigger of the revolver. The bullet crackles as the hammer rings, a thunderous bang that echoes through the branches of the tree. The sand grains hit the ground with a thud, echoing like a drum.\n", + "100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1133/1133 [1:20:24<00:00, 4.26s/it]\n", + " chinese ... unsloth/Qwen2-0.5B-Instruct-bnb-4bit\n", + "0 老耿端衷ζžͺοΌŒηœ―ηΌθ΅·δΈ€εͺδΈ‰θ§’ηœΌοΌŒδΈ€ζ‚ζ‰³ζœΊε“δΊ†ζžͺοΌŒε†°ι›Ήθˆ¬ηš„ι‡‘ιΊ»ι›€εŠˆε“©ε•ͺε•¦εΎ€δΈ‹θ½οΌŒι“η ‚ε­εœ¨ζŸ³ζžι—΄ι£ž... ... Old Tang raises his gun, half-closed eyes, fir...\n", + "\n", + "[1 rows x 7 columns]\n", + "(3) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "3.023 GB of memory reserved.\n", + "Unsloth 2024.6 patched 24 layers with 0 QKV layers, 24 O layers and 24 MLP layers.\n", + "/home/inflaton/miniconda3/envs/llm-fine-tune/lib/python3.11/site-packages/transformers/training_args.py:1965: FutureWarning: `--push_to_hub_token` is deprecated and will be removed in version 5 of πŸ€— Transformers. Use `--hub_token` instead.\n", + " warnings.warn(\n", + "/home/inflaton/miniconda3/envs/llm-fine-tune/lib/python3.11/site-packages/trl/trainer/sft_trainer.py:269: UserWarning: You passed a `max_seq_length` argument to the SFTTrainer, the value you passed will override the one in the `SFTConfig`.\n", + " warnings.warn(\n", + "/home/inflaton/miniconda3/envs/llm-fine-tune/lib/python3.11/site-packages/trl/trainer/sft_trainer.py:283: UserWarning: You passed a `dataset_num_proc` argument to the SFTTrainer, the value you passed will override the one in the `SFTConfig`.\n", + " warnings.warn(\n", + "/home/inflaton/miniconda3/envs/llm-fine-tune/lib/python3.11/site-packages/trl/trainer/sft_trainer.py:307: UserWarning: You passed a `dataset_text_field` argument to the SFTTrainer, the value you passed will override the one in the `SFTConfig`.\n", + " warnings.warn(\n", + "Map (num_proc=2): 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 4528/4528 [00:02<00:00, 2107.23 examples/s]\n", + "(4) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "3.023 GB of memory reserved.\n", + "==((====))== Unsloth - 2x faster free finetuning | Num GPUs = 1\n", + " \\\\ /| Num examples = 4,528 | Num Epochs = 10\n", + "O^O/ \\_/ \\ Batch size per device = 2 | Gradient Accumulation steps = 4\n", + "\\ / Total batch size = 8 | Total steps = 5,660\n", + " \"-____-\" Number of trainable parameters = 8,798,208\n", + "{'loss': 1.9402, 'grad_norm': 0.9608356952667236, 'learning_rate': 0.00019664014146772768, 'epoch': 0.18}\n", + "{'loss': 1.7759, 'grad_norm': 0.7993724346160889, 'learning_rate': 0.0001931034482758621, 'epoch': 0.35}\n", + "{'loss': 1.7139, 'grad_norm': 0.9072545766830444, 'learning_rate': 0.00018956675508399648, 'epoch': 0.53}\n", + "{'loss': 1.715, 'grad_norm': 0.7505761384963989, 'learning_rate': 0.00018603006189213086, 'epoch': 0.71}\n", + "{'loss': 1.6855, 'grad_norm': 0.819739580154419, 'learning_rate': 0.00018249336870026527, 'epoch': 0.88}\n", + "{'loss': 1.6071, 'grad_norm': 0.7929678559303284, 'learning_rate': 0.00017895667550839965, 'epoch': 1.06}\n", + "{'loss': 1.491, 'grad_norm': 0.8940563797950745, 'learning_rate': 0.00017541998231653406, 'epoch': 1.24}\n", + "{'loss': 1.5395, 'grad_norm': 0.9731950163841248, 'learning_rate': 0.00017188328912466844, 'epoch': 1.41}\n", + "{'loss': 1.4715, 'grad_norm': 1.0640537738800049, 'learning_rate': 0.00016834659593280285, 'epoch': 1.59}\n", + "{'loss': 1.4674, 'grad_norm': 0.9785354137420654, 'learning_rate': 0.00016480990274093723, 'epoch': 1.77}\n", + "{'loss': 1.5265, 'grad_norm': 1.007393479347229, 'learning_rate': 0.00016127320954907164, 'epoch': 1.94}\n", + "{'loss': 1.3483, 'grad_norm': 1.1656651496887207, 'learning_rate': 0.000157736516357206, 'epoch': 2.12}\n", + "{'loss': 1.2144, 'grad_norm': 1.1790250539779663, 'learning_rate': 0.0001541998231653404, 'epoch': 2.3}\n", + "{'loss': 1.2563, 'grad_norm': 1.3019884824752808, 'learning_rate': 0.0001506631299734748, 'epoch': 2.47}\n", + "{'loss': 1.2541, 'grad_norm': 1.2913496494293213, 'learning_rate': 0.0001471264367816092, 'epoch': 2.65}\n", + "{'loss': 1.2652, 'grad_norm': 1.15500009059906, 'learning_rate': 0.0001435897435897436, 'epoch': 2.83}\n", + "{'loss': 1.233, 'grad_norm': 1.1158246994018555, 'learning_rate': 0.000140053050397878, 'epoch': 3.0}\n", + "{'loss': 0.9784, 'grad_norm': 1.5188616514205933, 'learning_rate': 0.0001365163572060124, 'epoch': 3.18}\n", + "{'loss': 0.9898, 'grad_norm': 1.5216989517211914, 'learning_rate': 0.00013297966401414678, 'epoch': 3.36}\n", + "{'loss': 0.9973, 'grad_norm': 1.5246195793151855, 'learning_rate': 0.0001294429708222812, 'epoch': 3.53}\n", + "{'loss': 0.9778, 'grad_norm': 1.5367473363876343, 'learning_rate': 0.00012590627763041555, 'epoch': 3.71}\n", + "{'loss': 1.0212, 'grad_norm': 1.583097219467163, 'learning_rate': 0.00012236958443854996, 'epoch': 3.89}\n", + "{'loss': 0.9286, 'grad_norm': 1.4903535842895508, 'learning_rate': 0.00011883289124668435, 'epoch': 4.06}\n", + "{'loss': 0.7365, 'grad_norm': 1.7766040563583374, 'learning_rate': 0.00011529619805481875, 'epoch': 4.24}\n", + "{'loss': 0.7392, 'grad_norm': 1.7640079259872437, 'learning_rate': 0.00011175950486295315, 'epoch': 4.42}\n", + "{'loss': 0.772, 'grad_norm': 2.152620315551758, 'learning_rate': 0.00010822281167108754, 'epoch': 4.59}\n", + "{'loss': 0.7712, 'grad_norm': 2.200035333633423, 'learning_rate': 0.00010468611847922194, 'epoch': 4.77}\n", + "{'loss': 0.7922, 'grad_norm': 1.8203985691070557, 'learning_rate': 0.00010114942528735633, 'epoch': 4.95}\n", + "{'loss': 0.6284, 'grad_norm': 2.1231496334075928, 'learning_rate': 9.761273209549072e-05, 'epoch': 5.12}\n", + "{'loss': 0.5538, 'grad_norm': 1.633864402770996, 'learning_rate': 9.407603890362513e-05, 'epoch': 5.3}\n", + "{'loss': 0.5586, 'grad_norm': 1.8590402603149414, 'learning_rate': 9.053934571175951e-05, 'epoch': 5.48}\n", + "{'loss': 0.588, 'grad_norm': 1.8585463762283325, 'learning_rate': 8.70026525198939e-05, 'epoch': 5.65}\n", + "{'loss': 0.5816, 'grad_norm': 2.0347542762756348, 'learning_rate': 8.34659593280283e-05, 'epoch': 5.83}\n", + "{'loss': 0.5778, 'grad_norm': 1.9615962505340576, 'learning_rate': 7.99292661361627e-05, 'epoch': 6.01}\n", + "{'loss': 0.398, 'grad_norm': 1.861493468284607, 'learning_rate': 7.639257294429708e-05, 'epoch': 6.18}\n", + "{'loss': 0.4113, 'grad_norm': 1.8733363151550293, 'learning_rate': 7.285587975243147e-05, 'epoch': 6.36}\n", + "{'loss': 0.4295, 'grad_norm': 2.361309289932251, 'learning_rate': 6.931918656056587e-05, 'epoch': 6.54}\n", + "{'loss': 0.42, 'grad_norm': 1.871649980545044, 'learning_rate': 6.578249336870027e-05, 'epoch': 6.71}\n", + "{'loss': 0.4263, 'grad_norm': 1.567151427268982, 'learning_rate': 6.224580017683466e-05, 'epoch': 6.89}\n", + "{'loss': 0.3841, 'grad_norm': 1.7655881643295288, 'learning_rate': 5.870910698496905e-05, 'epoch': 7.07}\n", + "{'loss': 0.2916, 'grad_norm': 1.5300374031066895, 'learning_rate': 5.517241379310345e-05, 'epoch': 7.24}\n", + "{'loss': 0.3137, 'grad_norm': 1.399330973625183, 'learning_rate': 5.163572060123785e-05, 'epoch': 7.42}\n", + "{'loss': 0.3127, 'grad_norm': 2.009575605392456, 'learning_rate': 4.809902740937224e-05, 'epoch': 7.6}\n", + "{'loss': 0.3035, 'grad_norm': 1.74385404586792, 'learning_rate': 4.4562334217506634e-05, 'epoch': 7.77}\n", + "{'loss': 0.3187, 'grad_norm': 1.5835634469985962, 'learning_rate': 4.1025641025641023e-05, 'epoch': 7.95}\n", + "{'loss': 0.2469, 'grad_norm': 1.3062812089920044, 'learning_rate': 3.7488947833775426e-05, 'epoch': 8.13}\n", + "{'loss': 0.2274, 'grad_norm': 1.4867122173309326, 'learning_rate': 3.3952254641909815e-05, 'epoch': 8.3}\n", + "{'loss': 0.229, 'grad_norm': 1.0662896633148193, 'learning_rate': 3.041556145004421e-05, 'epoch': 8.48}\n", + "{'loss': 0.2378, 'grad_norm': 1.3190470933914185, 'learning_rate': 2.6878868258178604e-05, 'epoch': 8.66}\n", + "{'loss': 0.2362, 'grad_norm': 1.9712920188903809, 'learning_rate': 2.3342175066313e-05, 'epoch': 8.83}\n", + "{'loss': 0.238, 'grad_norm': 1.1038957834243774, 'learning_rate': 1.9805481874447392e-05, 'epoch': 9.01}\n", + "{'loss': 0.1807, 'grad_norm': 1.2336972951889038, 'learning_rate': 1.6268788682581788e-05, 'epoch': 9.19}\n", + "{'loss': 0.1896, 'grad_norm': 1.145556926727295, 'learning_rate': 1.273209549071618e-05, 'epoch': 9.36}\n", + "{'loss': 0.1878, 'grad_norm': 1.1361063718795776, 'learning_rate': 9.195402298850575e-06, 'epoch': 9.54}\n", + "{'loss': 0.189, 'grad_norm': 1.5798214673995972, 'learning_rate': 5.658709106984969e-06, 'epoch': 9.72}\n", + "{'loss': 0.19, 'grad_norm': 0.9943256974220276, 'learning_rate': 2.1220159151193635e-06, 'epoch': 9.89}\n", + "{'train_runtime': 13819.9366, 'train_samples_per_second': 3.276, 'train_steps_per_second': 0.41, 'train_loss': 0.7980813258949523, 'epoch': 10.0}\n", + "100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆοΏ½οΏ½οΏ½β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 5660/5660 [3:50:19<00:00, 2.44s/it]\n", + "(5) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "13819.9366 seconds used for training.\n", + "230.33 minutes used for training.\n", + "Peak reserved memory = 3.023 GB.\n", + "Peak reserved memory for training = 0.0 GB.\n", + "Peak reserved memory % of max memory = 25.204 %.\n", + "Peak reserved memory for training % of max memory = 0.0 %.\n", + "Evaluating fine-tuned model: unsloth/Qwen2-0.5B-Instruct-bnb-4bit\n", + " 0%| | 0/1133 [00:00\n", + "--------\n", + "step 2: Old Geng raised his rifle, clenching one of its triangular sights, and fired. A hailstone blast tore through the field, scattering large icy crickets (the cricket-like sounds of the gun wasp were like the crackles ofι’’ι“ηš„η’Žε—) that fell powerfully in the willows between them.\n", + "--------\n", + "step 3: Old Geng raised his rifle, clenching one of its triangular sights, and fired. A hailstone blast tore through the field, scattering large icy crickets (the cricket-like sounds of the gun wasp were like the crackles ofι’’ι“ηš„η’Žε—) that fell powerfully in the willows between them.\n", + "100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1133/1133 [1:48:52<00:00, 5.77s/it]\n", + " chinese ... unsloth/Qwen2-0.5B-Instruct-bnb-4bit(finetuned)\n", + "0 老耿端衷ζžͺοΌŒηœ―ηΌθ΅·δΈ€εͺδΈ‰θ§’ηœΌοΌŒδΈ€ζ‚ζ‰³ζœΊε“δΊ†ζžͺοΌŒε†°ι›Ήθˆ¬ηš„ι‡‘ιΊ»ι›€εŠˆε“©ε•ͺε•¦εΎ€δΈ‹θ½οΌŒι“η ‚ε­εœ¨ζŸ³ζžι—΄ι£ž... ... Old Geng raised his rifle, clenching one of it...\n", + "\n", + "[1 rows x 8 columns]\n", + "(6) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "4.344 GB of memory reserved.\n", + "model.safetensors: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 493M/493M [01:44<00:00, 4.71MB/s]\n", + "Saved model to https://huggingface.co/Qwen2-0.5B-Instruct-bnb-4bit-MAC-lora\n", + "README.md: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 599/599 [00:00<00:00, 3.50MB/s]\n", + "Unsloth: Saving tokenizer... Done.\n", + "Unsloth: Saving model... Done.\n", + "Unsloth: Saving LoRA adapters. Please wait...\n", + "401 Client Error: Unauthorized for url: https://huggingface.co/api/repos/create (Request ID: Root=1-667bdd5e-773cdcf53c89ad5261301688;d08e235b-a133-4e46-b5db-3e4f74133461)\n", + "\n", + "Invalid username or password.\n", + "Tuning unsloth/Qwen2-1.5B-Instruct-bnb-4bit\n", + "loading env vars from: /home/inflaton/code/projects/courses/llm-finetuning/.env\n", + "Adding /home/inflaton/code/projects/courses/llm-finetuning to sys.path\n", + "πŸ¦₯ Unsloth: Will patch your computer to enable 2x faster free finetuning.\n", + "[nltk_data] Downloading package wordnet to /home/inflaton/nltk_data...\n", + "[nltk_data] Package wordnet is already up-to-date!\n", + "[nltk_data] Downloading package punkt to /home/inflaton/nltk_data...\n", + "[nltk_data] Package punkt is already up-to-date!\n", + "[nltk_data] Downloading package omw-1.4 to /home/inflaton/nltk_data...\n", + "[nltk_data] Package omw-1.4 is already up-to-date!\n", + "loading /home/inflaton/code/projects/courses/llm-finetuning/llm_toolkit/translation_engine.py\n", + "unsloth/Qwen2-1.5B-Instruct-bnb-4bit True 2048 10 None datasets/mac/mac.tsv results/mac-results_py3.11.csv True True True\n", + "(1) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "0.0 GB of memory reserved.\n", + "loading model: unsloth/Qwen2-1.5B-Instruct-bnb-4bit\n", + "==((====))== Unsloth: Fast Qwen2 patching release 2024.6\n", + " \\\\ /| GPU: NVIDIA GeForce RTX 4080 Laptop GPU. Max memory: 11.994 GB. Platform = Linux.\n", + "O^O/ \\_/ \\ Pytorch: 2.3.0+cu121. CUDA = 8.9. CUDA Toolkit = 12.1.\n", + "\\ / Bfloat16 = TRUE. Xformers = 0.0.26.post1. FA = False.\n", + " \"-____-\" Free Apache license: http://github.com/unslothai/unsloth\n", + "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", + "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", + "(2) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "1.516 GB of memory reserved.\n", + "loading train/test data files\n", + "Map: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 4528/4528 [00:00<00:00, 10965.65 examples/s]\n", + "Map: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1133/1133 [00:00<00:00, 9010.28 examples/s]\n", + "DatasetDict({\n", + " train: Dataset({\n", + " features: ['chinese', 'english', 'text', 'prompt'],\n", + " num_rows: 4528\n", + " })\n", + " test: Dataset({\n", + " features: ['chinese', 'english', 'text', 'prompt'],\n", + " num_rows: 1133\n", + " })\n", + "})\n", + "Evaluating base model: unsloth/Qwen2-1.5B-Instruct-bnb-4bit\n", + " 0%| | 0/1133 [00:00\n", + "--------\n", + "step 2: Oldθ€Ώζ‹Ώθ΅·ζžͺοΌŒηœ―ηΌθ΅·δΈ€εͺδΈ‰θ§’ηœΌοΌŒδΈ€ζ‚ζ‰³ζœΊε“δΊ†ζžͺοΌŒε†°ι›Ήθˆ¬ηš„ι‡‘ιΊ»ι›€εŠˆε“©ε•ͺε•¦εΎ€δΈ‹θ½οΌŒι“η ‚ε­εœ¨ζŸ³ζžι—΄ι£žθΏΈη€οΌŒεš“εš“ζœ‰ε£°γ€‚\n", + "--------\n", + "step 3: Oldθ€Ώζ‹Ώθ΅·ζžͺοΌŒηœ―ηΌθ΅·δΈ€εͺδΈ‰θ§’ηœΌοΌŒδΈ€ζ‚ζ‰³ζœΊε“δΊ†ζžͺοΌŒε†°ι›Ήθˆ¬ηš„ι‡‘ιΊ»ι›€εŠˆε“©ε•ͺε•¦εΎ€δΈ‹θ½οΌŒι“η ‚ε­εœ¨ζŸ³ζžι—΄ι£žθΏΈη€οΌŒεš“εš“ζœ‰ε£°γ€‚\n", + "100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1133/1133 [1:09:28<00:00, 3.68s/it]\n", + " chinese ... unsloth/Qwen2-1.5B-Instruct-bnb-4bit\n", + "0 老耿端衷ζžͺοΌŒηœ―ηΌθ΅·δΈ€εͺδΈ‰θ§’ηœΌοΌŒδΈ€ζ‚ζ‰³ζœΊε“δΊ†ζžͺοΌŒε†°ι›Ήθˆ¬ηš„ι‡‘ιΊ»ι›€εŠˆε“©ε•ͺε•¦εΎ€δΈ‹θ½οΌŒι“η ‚ε­εœ¨ζŸ³ζžι—΄ι£ž... ... Oldθ€Ώζ‹Ώθ΅·ζžͺοΌŒηœ―ηΌθ΅·δΈ€εͺδΈ‰θ§’ηœΌοΌŒδΈ€ζ‚ζ‰³ζœΊε“δΊ†ζžͺοΌŒε†°ι›Ήθˆ¬ηš„ι‡‘ιΊ»ι›€εŠˆε“©ε•ͺε•¦εΎ€δΈ‹θ½οΌŒι“η ‚ε­εœ¨ζŸ³ζž...\n", + "\n", + "[1 rows x 9 columns]\n", + "(3) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "1.758 GB of memory reserved.\n", + "Unsloth 2024.6 patched 28 layers with 0 QKV layers, 28 O layers and 28 MLP layers.\n", + "/home/inflaton/miniconda3/envs/llm-fine-tune/lib/python3.11/site-packages/transformers/training_args.py:1965: FutureWarning: `--push_to_hub_token` is deprecated and will be removed in version 5 of πŸ€— Transformers. Use `--hub_token` instead.\n", + " warnings.warn(\n", + "/home/inflaton/miniconda3/envs/llm-fine-tune/lib/python3.11/site-packages/trl/trainer/sft_trainer.py:269: UserWarning: You passed a `max_seq_length` argument to the SFTTrainer, the value you passed will override the one in the `SFTConfig`.\n", + " warnings.warn(\n", + "/home/inflaton/miniconda3/envs/llm-fine-tune/lib/python3.11/site-packages/trl/trainer/sft_trainer.py:283: UserWarning: You passed a `dataset_num_proc` argument to the SFTTrainer, the value you passed will override the one in the `SFTConfig`.\n", + " warnings.warn(\n", + "/home/inflaton/miniconda3/envs/llm-fine-tune/lib/python3.11/site-packages/trl/trainer/sft_trainer.py:307: UserWarning: You passed a `dataset_text_field` argument to the SFTTrainer, the value you passed will override the one in the `SFTConfig`.\n", + " warnings.warn(\n", + "Map (num_proc=2): 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 4528/4528 [00:02<00:00, 2245.59 examples/s]\n", + "(4) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "1.758 GB of memory reserved.\n", + "==((====))== Unsloth - 2x faster free finetuning | Num GPUs = 1\n", + " \\\\ /| Num examples = 4,528 | Num Epochs = 10\n", + "O^O/ \\_/ \\ Batch size per device = 2 | Gradient Accumulation steps = 4\n", + "\\ / Total batch size = 8 | Total steps = 5,660\n", + " \"-____-\" Number of trainable parameters = 18,464,768\n", + "{'loss': 1.7415, 'grad_norm': 0.6513338088989258, 'learning_rate': 0.00019664014146772768, 'epoch': 0.18}\n", + "{'loss': 1.5683, 'grad_norm': 0.6299685835838318, 'learning_rate': 0.0001931034482758621, 'epoch': 0.35}\n", + "{'loss': 1.5159, 'grad_norm': 0.6519908905029297, 'learning_rate': 0.00018956675508399648, 'epoch': 0.53}\n", + "{'loss': 1.5172, 'grad_norm': 0.580685019493103, 'learning_rate': 0.00018603006189213086, 'epoch': 0.71}\n", + "{'loss': 1.496, 'grad_norm': 0.5678043365478516, 'learning_rate': 0.00018249336870026527, 'epoch': 0.88}\n", + "{'loss': 1.4184, 'grad_norm': 0.6064684987068176, 'learning_rate': 0.00017895667550839965, 'epoch': 1.06}\n", + "{'loss': 1.2976, 'grad_norm': 0.7216887474060059, 'learning_rate': 0.00017541998231653406, 'epoch': 1.24}\n", + "{'loss': 1.3393, 'grad_norm': 0.6848570108413696, 'learning_rate': 0.00017188328912466844, 'epoch': 1.41}\n", + "{'loss': 1.2784, 'grad_norm': 0.9106780886650085, 'learning_rate': 0.00016834659593280285, 'epoch': 1.59}\n", + "{'loss': 1.2801, 'grad_norm': 0.8649025559425354, 'learning_rate': 0.00016480990274093723, 'epoch': 1.77}\n", + "{'loss': 1.3313, 'grad_norm': 0.880467414855957, 'learning_rate': 0.00016127320954907164, 'epoch': 1.94}\n", + "{'loss': 1.1276, 'grad_norm': 1.0269683599472046, 'learning_rate': 0.000157736516357206, 'epoch': 2.12}\n", + "{'loss': 0.9956, 'grad_norm': 1.0964370965957642, 'learning_rate': 0.0001541998231653404, 'epoch': 2.3}\n", + "{'loss': 1.0299, 'grad_norm': 1.298215389251709, 'learning_rate': 0.0001506631299734748, 'epoch': 2.47}\n", + "{'loss': 1.0348, 'grad_norm': 1.1091656684875488, 'learning_rate': 0.0001471264367816092, 'epoch': 2.65}\n", + "{'loss': 1.0346, 'grad_norm': 1.0557124614715576, 'learning_rate': 0.0001435897435897436, 'epoch': 2.83}\n", + "{'loss': 1.0081, 'grad_norm': 0.8857123255729675, 'learning_rate': 0.000140053050397878, 'epoch': 3.0}\n", + "{'loss': 0.6977, 'grad_norm': 1.3270587921142578, 'learning_rate': 0.0001365163572060124, 'epoch': 3.18}\n", + "{'loss': 0.7104, 'grad_norm': 1.3964347839355469, 'learning_rate': 0.00013297966401414678, 'epoch': 3.36}\n", + "{'loss': 0.7135, 'grad_norm': 1.324993371963501, 'learning_rate': 0.0001294429708222812, 'epoch': 3.53}\n", + "{'loss': 0.7054, 'grad_norm': 1.4066098928451538, 'learning_rate': 0.00012590627763041555, 'epoch': 3.71}\n", + "{'loss': 0.7424, 'grad_norm': 1.287760615348816, 'learning_rate': 0.00012236958443854996, 'epoch': 3.89}\n", + "{'loss': 0.6421, 'grad_norm': 1.2553821802139282, 'learning_rate': 0.00011883289124668435, 'epoch': 4.06}\n", + "{'loss': 0.4585, 'grad_norm': 1.6327370405197144, 'learning_rate': 0.00011529619805481875, 'epoch': 4.24}\n", + "{'loss': 0.4444, 'grad_norm': 1.6593241691589355, 'learning_rate': 0.00011175950486295315, 'epoch': 4.42}\n", + "{'loss': 0.4802, 'grad_norm': 1.5733627080917358, 'learning_rate': 0.00010822281167108754, 'epoch': 4.59}\n", + "{'loss': 0.4779, 'grad_norm': 1.6328530311584473, 'learning_rate': 0.00010468611847922194, 'epoch': 4.77}\n", + "{'loss': 0.4873, 'grad_norm': 1.664158582687378, 'learning_rate': 0.00010114942528735633, 'epoch': 4.95}\n", + "{'loss': 0.3602, 'grad_norm': 1.923504114151001, 'learning_rate': 9.761273209549072e-05, 'epoch': 5.12}\n", + "{'loss': 0.2924, 'grad_norm': 1.2101478576660156, 'learning_rate': 9.407603890362513e-05, 'epoch': 5.3}\n", + "{'loss': 0.2975, 'grad_norm': 1.3352692127227783, 'learning_rate': 9.053934571175951e-05, 'epoch': 5.48}\n", + "{'loss': 0.3142, 'grad_norm': 1.528309941291809, 'learning_rate': 8.70026525198939e-05, 'epoch': 5.65}\n", + "{'loss': 0.306, 'grad_norm': 1.3299399614334106, 'learning_rate': 8.34659593280283e-05, 'epoch': 5.83}\n", + "{'loss': 0.3081, 'grad_norm': 0.5754266381263733, 'learning_rate': 7.99292661361627e-05, 'epoch': 6.01}\n", + "{'loss': 0.1935, 'grad_norm': 1.24480402469635, 'learning_rate': 7.639257294429708e-05, 'epoch': 6.18}\n", + "{'loss': 0.2045, 'grad_norm': 1.5091683864593506, 'learning_rate': 7.285587975243147e-05, 'epoch': 6.36}\n", + "{'loss': 0.2071, 'grad_norm': 0.9175063371658325, 'learning_rate': 6.931918656056587e-05, 'epoch': 6.54}\n", + "{'loss': 0.2055, 'grad_norm': 1.013519525527954, 'learning_rate': 6.578249336870027e-05, 'epoch': 6.71}\n", + "{'loss': 0.2133, 'grad_norm': 2.126910448074341, 'learning_rate': 6.224580017683466e-05, 'epoch': 6.89}\n", + "{'loss': 0.194, 'grad_norm': 0.8879603147506714, 'learning_rate': 5.870910698496905e-05, 'epoch': 7.07}\n", + "{'loss': 0.149, 'grad_norm': 0.7381364107131958, 'learning_rate': 5.517241379310345e-05, 'epoch': 7.24}\n", + "{'loss': 0.1564, 'grad_norm': 0.7718709111213684, 'learning_rate': 5.163572060123785e-05, 'epoch': 7.42}\n", + "{'loss': 0.1573, 'grad_norm': 0.6855681538581848, 'learning_rate': 4.809902740937224e-05, 'epoch': 7.6}\n", + "{'loss': 0.1578, 'grad_norm': 0.9972281455993652, 'learning_rate': 4.4562334217506634e-05, 'epoch': 7.77}\n", + "{'loss': 0.1588, 'grad_norm': 0.818317174911499, 'learning_rate': 4.1025641025641023e-05, 'epoch': 7.95}\n", + "{'loss': 0.1375, 'grad_norm': 0.46658992767333984, 'learning_rate': 3.7488947833775426e-05, 'epoch': 8.13}\n", + "{'loss': 0.1304, 'grad_norm': 0.5777143836021423, 'learning_rate': 3.3952254641909815e-05, 'epoch': 8.3}\n", + "{'loss': 0.1315, 'grad_norm': 0.4499460756778717, 'learning_rate': 3.041556145004421e-05, 'epoch': 8.48}\n", + "{'loss': 0.1327, 'grad_norm': 0.4142455756664276, 'learning_rate': 2.6878868258178604e-05, 'epoch': 8.66}\n", + "{'loss': 0.1337, 'grad_norm': 0.6300601959228516, 'learning_rate': 2.3342175066313e-05, 'epoch': 8.83}\n", + "{'loss': 0.1327, 'grad_norm': 0.4785163998603821, 'learning_rate': 1.9805481874447392e-05, 'epoch': 9.01}\n", + "{'loss': 0.1178, 'grad_norm': 0.4512840211391449, 'learning_rate': 1.6268788682581788e-05, 'epoch': 9.19}\n", + "{'loss': 0.1186, 'grad_norm': 0.5308012366294861, 'learning_rate': 1.273209549071618e-05, 'epoch': 9.36}\n", + "{'loss': 0.1195, 'grad_norm': 0.4567421078681946, 'learning_rate': 9.195402298850575e-06, 'epoch': 9.54}\n", + "{'loss': 0.1203, 'grad_norm': 0.68560391664505, 'learning_rate': 5.658709106984969e-06, 'epoch': 9.72}\n", + "{'loss': 0.1231, 'grad_norm': 0.41683992743492126, 'learning_rate': 2.1220159151193635e-06, 'epoch': 9.89}\n", + "{'train_runtime': 16113.2955, 'train_samples_per_second': 2.81, 'train_steps_per_second': 0.351, 'train_loss': 0.5992827712857681, 'epoch': 10.0}\n", + "100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 5660/5660 [4:28:33<00:00, 2.85s/it]\n", + "(5) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "16113.2955 seconds used for training.\n", + "268.55 minutes used for training.\n", + "Peak reserved memory = 2.367 GB.\n", + "Peak reserved memory for training = 0.609 GB.\n", + "Peak reserved memory % of max memory = 19.735 %.\n", + "Peak reserved memory for training % of max memory = 5.078 %.\n", + "Evaluating fine-tuned model: unsloth/Qwen2-1.5B-Instruct-bnb-4bit\n", + " 0%| | 0/1133 [00:00\n", + "--------\n", + "step 2: Old Geng raised his pistol, cocked it, and fired – a string of pocky-gun shots sent the shooting birds skittering to the ground.\n", + "--------\n", + "step 3: Old Geng raised his pistol, cocked it, and fired – a string of pocky-gun shots sent the shooting birds skittering to the ground.\n", + "100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1133/1133 [1:44:47<00:00, 5.55s/it]\n", + " chinese ... unsloth/Qwen2-1.5B-Instruct-bnb-4bit(finetuned)\n", + "0 老耿端衷ζžͺοΌŒηœ―ηΌθ΅·δΈ€εͺδΈ‰θ§’ηœΌοΌŒδΈ€ζ‚ζ‰³ζœΊε“δΊ†ζžͺοΌŒε†°ι›Ήθˆ¬ηš„ι‡‘ιΊ»ι›€εŠˆε“©ε•ͺε•¦εΎ€δΈ‹θ½οΌŒι“η ‚ε­εœ¨ζŸ³ζžι—΄ι£ž... ... Old Geng raised his pistol, cocked it, and fir...\n", + "\n", + "[1 rows x 10 columns]\n", + "(6) GPU = NVIDIA GeForce RTX 4080 Laptop GPU. Max memory = 11.994 GB.\n", + "2.367 GB of memory reserved.\n", + "model.safetensors: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1.22G/1.22G [04:55<00:00, 4.12MB/s]\n", + "Saved model to https://huggingface.co/Qwen2-1.5B-Instruct-bnb-4bit-MAC-lora\n", + "README.md: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 599/599 [00:00<00:00, 2.91MB/s]\n", + "Unsloth: Saving tokenizer... Done.\n", + "Unsloth: Saving model... Done.\n", + "Unsloth: Saving LoRA adapters. Please wait...\n", + "401 Client Error: Unauthorized for url: https://huggingface.co/api/repos/create (Request ID: Root=1-667c46cc-179d7b0b46deeb6521c1ce66;676583ba-2144-4b1c-928b-aafd3708580e)\n", + "\n", + "Invalid username or password.\n", + "CPU times: user 20min 59s, sys: 8min 13s, total: 29min 13s\n", + "Wall time: 14h 32min 29s\n" + ] + } + ], + "source": [ + "%%time\n", + "\n", + "!./scripts/tune-small.sh" + ] + } + ], + "metadata": { + "accelerator": "GPU", + "application/vnd.databricks.v1+notebook": { + "dashboards": [], + "environmentMetadata": null, + "language": "python", + "notebookMetadata": { + "pythonIndentUnit": 4 + }, + "notebookName": "07_MAC_+_Qwen2-7B-Instructi_Unsloth_train", + "widgets": {} + }, + "colab": { + "gpuType": "T4", + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.1.-1" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "036fc5746f43416db18c19ad8fd36677": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "06e806c82c7b4cbea31c5358dd9c3434": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "087b76a8b7514269b1f0ab29b062e444": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_a069d2ab23824f29aa320ac256e2cfe9", + "placeholder": "​", + "style": "IPY_MODEL_06e806c82c7b4cbea31c5358dd9c3434", + "value": "Map (num_proc=2): 100%" + } + }, + "09b76013aa9e45efb6deb23a7a0d0925": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_dea41c5260884aa6879b5e1d1697b14f", + "placeholder": "​", + "style": "IPY_MODEL_89965917796a4f81b899fdc7685f33df", + "value": "config.json: 100%" + } + }, + "0a92c56bfa134ef583220d7ef0b13e17": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "0c34be936c8145d3ab41282f30a70713": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "0f8b6bfe16894500838793f2491d403f": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "177c78fce95d4b4ab33057c5a048d693": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "1f44c9ce1adf470cbb19784493ed209f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_0c34be936c8145d3ab41282f30a70713", + "placeholder": "​", + "style": "IPY_MODEL_0a92c56bfa134ef583220d7ef0b13e17", + "value": "model.safetensors: 100%" + } + }, + "201b59ccd9f845e197029b57e424aefc": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "2157f01726d748f8a9ae4a00664430da": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "21db8a77b00d4a4e82fdfa608657531f": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "26e4202cca81496a90d15a0dd4ca9cf1": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_ba90fdb8822d47dab7ba203bee297f37", + "IPY_MODEL_61560ff6a36b44f4a9dfdae5c52791d4", + "IPY_MODEL_95fbe66647904c06a20f640630d6dc0e" + ], + "layout": "IPY_MODEL_57182a263d324a3dbf1471c74290a0d5" + } + }, + "27155728b6b84cb199c91c940095d0a8": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_6b91feeed5464877991ac2c207aebe7c", + "IPY_MODEL_cca8113c54c0495daedce1327bf9c68b", + "IPY_MODEL_2e63a29e2f7247bba5beede9a568c99f" + ], + "layout": "IPY_MODEL_5c9d781c28944f3eb86e2a6d44efdf18" + } + }, + "271ddaa553a042d09b6db7b450643d8f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "2a58d04b428c46f4b3dbadd3bc6cd529": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "2d18ddf6482c4d97829ac0e5a7b9868f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_9f679ad3ec7f4fe8ad0510ffb57bc2ab", + "IPY_MODEL_f2df530d22c74977b249dd9fb5f4829b", + "IPY_MODEL_89b2ef0dbfea47ab8e6f8d659e3351d1" + ], + "layout": "IPY_MODEL_3056b148aa9f4e6e8aa3b61d26886255" + } + }, + "2e5087c76f98437cb5dc729230358cba": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "2e63a29e2f7247bba5beede9a568c99f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_b993eaec6b224440bf80c0958c6fb536", + "placeholder": "​", + "style": "IPY_MODEL_de868e26e7154f62aa86223a539ad421", + "value": " 464/464 [00:00<00:00, 27.1kB/s]" + } + }, + "2f6c70dd266c4816bfad3fd3d192929a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "30307300bc4e4baf96560e30969a82b6": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_e36a3f9eff0e4cf68834d66b0213ae96", + "placeholder": "​", + "style": "IPY_MODEL_a0037bdccf254159becde630bee3d1db", + "value": "generation_config.json: 100%" + } + }, + "3056b148aa9f4e6e8aa3b61d26886255": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "30cdc32298134cb0be4d41615b9e5774": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "3572201bd4d74a58b7a665f9bdfdcdba": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "35b0e8c26d6640e9bd0ed7b242a423d8": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_2e5087c76f98437cb5dc729230358cba", + "max": 51760, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_036fc5746f43416db18c19ad8fd36677", + "value": 51760 + } + }, + "36166c7bcb854b34aca1f41a5d6ea50b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "370692d819df41828b48c4ad446f977b": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "39b29a75374b45c0a22506010be2b84e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_30cdc32298134cb0be4d41615b9e5774", + "max": 1179, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_47928317548c454bba6358ab132e8dee", + "value": 1179 + } + }, + "3cf2dd993b5e4d3daecf61e4bab5a404": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_087b76a8b7514269b1f0ab29b062e444", + "IPY_MODEL_35b0e8c26d6640e9bd0ed7b242a423d8", + "IPY_MODEL_54ad89e05fd74576b9b8b5b5a10eaf8d" + ], + "layout": "IPY_MODEL_a41dc44766444a998bec2d777f249d23" + } + }, + "43dec2ede91341f5af60eb522e18e984": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "4463edd481c1467f914c7dcd6c6e6ffc": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "47928317548c454bba6358ab132e8dee": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "49277aeeac16434a865a4d12308b1abc": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "4ae7e449e4ea4c729b5f34607c18ebae": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "4b2061b8a73c43ffb0c2f83daf0d0183": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "4c4c88d4c701450692fa0f6b0c5764b0": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "4c666f4ace3943f8b80ecd20e7503236": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "4ccedf0d93094e63b57a0f8a434fba06": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_4463edd481c1467f914c7dcd6c6e6ffc", + "max": 44307561, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_6d3b9a05db0b4dadb638c686faa0c40a", + "value": 44307561 + } + }, + "4dcf6ff672d24983a1877a8431709aa9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_5807d5fb827d490fb3bc698f801ffff5", + "placeholder": "​", + "style": "IPY_MODEL_c4f2b06a82fd4987b8b659524a7b503b", + "value": "Generating train split: 100%" + } + }, + "4ea63adfce694725bdba878aef709dd3": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "5234566b1bfc4655b8d582ea5b46ed9f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "54ad89e05fd74576b9b8b5b5a10eaf8d": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_fdb1941405ed4e4aa06019933892deb3", + "placeholder": "​", + "style": "IPY_MODEL_668d5377ca56426a99753867e6e24862", + "value": " 51760/51760 [01:02<00:00, 1131.51 examples/s]" + } + }, + "56aee4853b7740e6a977254f5d1fa66d": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "57182a263d324a3dbf1471c74290a0d5": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "5807d5fb827d490fb3bc698f801ffff5": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "5c9d781c28944f3eb86e2a6d44efdf18": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "5f40db8173dd4d76b6ef5ed6d9ec8b6e": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "61560ff6a36b44f4a9dfdae5c52791d4": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_db19fc8d37db4e45a5790a876836d8c4", + "max": 11610, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_36166c7bcb854b34aca1f41a5d6ea50b", + "value": 11610 + } + }, + "6578fd7acdb54c4c93528ea431fd0144": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_370692d819df41828b48c4ad446f977b", + "placeholder": "​", + "style": "IPY_MODEL_a0bf9160eb2647409b3200270914b90f", + "value": " 50.6k/50.6k [00:00<00:00, 2.71MB/s]" + } + }, + "668d5377ca56426a99753867e6e24862": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "697f027529b54ee9956bae78a11e0611": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "69ac12aec0714318bf2c83d4f4e745f5": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "6b2012c3f88547af8884a9ea90e3164b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_938f45f1b3e24118b815d96ae34ba86a", + "placeholder": "​", + "style": "IPY_MODEL_9367047a800747f79c6b225d92397846", + "value": " 44.3M/44.3M [00:01<00:00, 31.0MB/s]" + } + }, + "6b91feeed5464877991ac2c207aebe7c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_4b2061b8a73c43ffb0c2f83daf0d0183", + "placeholder": "​", + "style": "IPY_MODEL_69ac12aec0714318bf2c83d4f4e745f5", + "value": "special_tokens_map.json: 100%" + } + }, + "6d3b9a05db0b4dadb638c686faa0c40a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "6dbbedeca9314e66ae50e44ffa31a414": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "6e34619b45934040b6092e6fb01ea7fe": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "71ce208e20d6483abb9ed923510c86d7": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_d69dc491b3ab44d7852b21873ed7bb7f", + "placeholder": "​", + "style": "IPY_MODEL_f401d53bf28e44eb906bce6c05412662", + "value": " 51760/51760 [00:01<00:00, 45512.81 examples/s]" + } + }, + "7358cdad832342c983e31efb8754ab78": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "73e352a3404f4c7dad0737f57d29e92f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_988a0e8c1f89446086858da0a891a79c", + "IPY_MODEL_4ccedf0d93094e63b57a0f8a434fba06", + "IPY_MODEL_6b2012c3f88547af8884a9ea90e3164b" + ], + "layout": "IPY_MODEL_7e29cb8dd4df4d5b94407cd8fd3f2011" + } + }, + "74501720ac7e4dbb911a4a99b3633bc6": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "78e5400bff924a92a4cc61c4ff18b182": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_b9b313fd861948f5aba25b24b1518d30", + "placeholder": "​", + "style": "IPY_MODEL_4c666f4ace3943f8b80ecd20e7503236", + "value": " 1.18k/1.18k [00:00<00:00, 31.3kB/s]" + } + }, + "7975adbc2ec5489ea7fa0167e620d85c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_6e34619b45934040b6092e6fb01ea7fe", + "max": 51760, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_271ddaa553a042d09b6db7b450643d8f", + "value": 51760 + } + }, + "7e29cb8dd4df4d5b94407cd8fd3f2011": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "810ff6c0e17d4fa09a30fef27eacff90": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "89965917796a4f81b899fdc7685f33df": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "89b2ef0dbfea47ab8e6f8d659e3351d1": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_b8908fa0df3743ecb9d12983a739104f", + "placeholder": "​", + "style": "IPY_MODEL_177c78fce95d4b4ab33057c5a048d693", + "value": " 9.09M/9.09M [00:00<00:00, 32.6MB/s]" + } + }, + "8b3505352a5a42bf910428c40ce40465": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_49277aeeac16434a865a4d12308b1abc", + "placeholder": "​", + "style": "IPY_MODEL_2157f01726d748f8a9ae4a00664430da", + "value": " 5.70G/5.70G [01:02<00:00, 30.1MB/s]" + } + }, + "8fc142b628fb40568730234de1cafde2": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_4ae7e449e4ea4c729b5f34607c18ebae", + "max": 172, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_3572201bd4d74a58b7a665f9bdfdcdba", + "value": 172 + } + }, + "9367047a800747f79c6b225d92397846": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "938f45f1b3e24118b815d96ae34ba86a": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "95fbe66647904c06a20f640630d6dc0e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_b0a370dc20654b279b9680692e34418e", + "placeholder": "​", + "style": "IPY_MODEL_cfeb365ddf7548d58b2557f22737fcf5", + "value": " 11.6k/11.6k [00:00<00:00, 716kB/s]" + } + }, + "988a0e8c1f89446086858da0a891a79c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_ad2be500fc164c0f86f33e914ef8e6a0", + "placeholder": "​", + "style": "IPY_MODEL_5234566b1bfc4655b8d582ea5b46ed9f", + "value": "Downloading data: 100%" + } + }, + "98c58f23f4d549518832cb2d18f796e8": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_09b76013aa9e45efb6deb23a7a0d0925", + "IPY_MODEL_39b29a75374b45c0a22506010be2b84e", + "IPY_MODEL_78e5400bff924a92a4cc61c4ff18b182" + ], + "layout": "IPY_MODEL_2a58d04b428c46f4b3dbadd3bc6cd529" + } + }, + "99fdbb0300c14c139d1937c646f0cfe7": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_7358cdad832342c983e31efb8754ab78", + "placeholder": "​", + "style": "IPY_MODEL_e9adf418296e436fb48bb9f78885598b", + "value": " 51760/51760 [00:01<00:00, 38665.95 examples/s]" + } + }, + "9f679ad3ec7f4fe8ad0510ffb57bc2ab": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_4ea63adfce694725bdba878aef709dd3", + "placeholder": "​", + "style": "IPY_MODEL_74501720ac7e4dbb911a4a99b3633bc6", + "value": "tokenizer.json: 100%" + } + }, + "a0037bdccf254159becde630bee3d1db": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "a069d2ab23824f29aa320ac256e2cfe9": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "a0bf9160eb2647409b3200270914b90f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "a41dc44766444a998bec2d777f249d23": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "a8464a4c711e4e00aafdfc919b60d07e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_fb995c740590427b882572c81d4e848c", + "placeholder": "​", + "style": "IPY_MODEL_201b59ccd9f845e197029b57e424aefc", + "value": " 172/172 [00:00<00:00, 12.0kB/s]" + } + }, + "a9f0cc51fc3d4d7b874c32dcf1c5bdf2": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "ad2be500fc164c0f86f33e914ef8e6a0": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "b0240cd9a4554b29ae11f8051984a1c6": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_edaf890370314a218f138015faa0b05d", + "placeholder": "​", + "style": "IPY_MODEL_697f027529b54ee9956bae78a11e0611", + "value": "Map: 100%" + } + }, + "b0a370dc20654b279b9680692e34418e": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "b518dcee69074b87be73957cd810e7ed": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_d891f8d0b1fc462f8008d02bb2a15692", + "placeholder": "​", + "style": "IPY_MODEL_cced8fd7e998472794f3f3e3018956a5", + "value": "tokenizer_config.json: 100%" + } + }, + "b8908fa0df3743ecb9d12983a739104f": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "b993eaec6b224440bf80c0958c6fb536": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "b9b313fd861948f5aba25b24b1518d30": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "ba90fdb8822d47dab7ba203bee297f37": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_0f8b6bfe16894500838793f2491d403f", + "placeholder": "​", + "style": "IPY_MODEL_bb19f6c747754682a514373a3a0535ba", + "value": "Downloading readme: 100%" + } + }, + "bb19f6c747754682a514373a3a0535ba": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "bc883d4cf13e4f8b8a4fe5f410cb6efd": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_e9159e03e61f4f56978ece9c3bca49b2", + "max": 51760, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_810ff6c0e17d4fa09a30fef27eacff90", + "value": 51760 + } + }, + "c161d94df0f04feba9542237e0856c22": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "c22f71b1f85843209d7e5321506b9cb9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_1f44c9ce1adf470cbb19784493ed209f", + "IPY_MODEL_f1addc4479d849879e743cf9089e6540", + "IPY_MODEL_8b3505352a5a42bf910428c40ce40465" + ], + "layout": "IPY_MODEL_4c4c88d4c701450692fa0f6b0c5764b0" + } + }, + "c4f2b06a82fd4987b8b659524a7b503b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "cca8113c54c0495daedce1327bf9c68b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_e02f9b7849c64531835eb77b860d1c93", + "max": 464, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_56aee4853b7740e6a977254f5d1fa66d", + "value": 464 + } + }, + "cced8fd7e998472794f3f3e3018956a5": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "cf245afeb1c04f29a24d291608c3d157": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_b518dcee69074b87be73957cd810e7ed", + "IPY_MODEL_e29104486d594b2992d7285e0ef77371", + "IPY_MODEL_6578fd7acdb54c4c93528ea431fd0144" + ], + "layout": "IPY_MODEL_d35db8148a354c56aaac56dbae22536f" + } + }, + "cfe8cae0e22b495bafa221a63d13b283": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "cfeb365ddf7548d58b2557f22737fcf5": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "d1b47d39450d4019ae85c9b2f943eeaf": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_4dcf6ff672d24983a1877a8431709aa9", + "IPY_MODEL_7975adbc2ec5489ea7fa0167e620d85c", + "IPY_MODEL_71ce208e20d6483abb9ed923510c86d7" + ], + "layout": "IPY_MODEL_cfe8cae0e22b495bafa221a63d13b283" + } + }, + "d35db8148a354c56aaac56dbae22536f": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "d69dc491b3ab44d7852b21873ed7bb7f": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "d891f8d0b1fc462f8008d02bb2a15692": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "d8e5318cead340c4adbeaccc05d39225": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "daf4cd890b35422683d22fd30bc71e83": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_b0240cd9a4554b29ae11f8051984a1c6", + "IPY_MODEL_bc883d4cf13e4f8b8a4fe5f410cb6efd", + "IPY_MODEL_99fdbb0300c14c139d1937c646f0cfe7" + ], + "layout": "IPY_MODEL_c161d94df0f04feba9542237e0856c22" + } + }, + "db19fc8d37db4e45a5790a876836d8c4": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "de868e26e7154f62aa86223a539ad421": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "dea41c5260884aa6879b5e1d1697b14f": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "e02f9b7849c64531835eb77b860d1c93": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "e29104486d594b2992d7285e0ef77371": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_a9f0cc51fc3d4d7b874c32dcf1c5bdf2", + "max": 50641, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_2f6c70dd266c4816bfad3fd3d192929a", + "value": 50641 + } + }, + "e36a3f9eff0e4cf68834d66b0213ae96": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "e9159e03e61f4f56978ece9c3bca49b2": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "e9adf418296e436fb48bb9f78885598b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "edaf890370314a218f138015faa0b05d": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "f1addc4479d849879e743cf9089e6540": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_43dec2ede91341f5af60eb522e18e984", + "max": 5702746405, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_d8e5318cead340c4adbeaccc05d39225", + "value": 5702746405 + } + }, + "f2df530d22c74977b249dd9fb5f4829b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_21db8a77b00d4a4e82fdfa608657531f", + "max": 9085698, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_6dbbedeca9314e66ae50e44ffa31a414", + "value": 9085698 + } + }, + "f401d53bf28e44eb906bce6c05412662": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "fb995c740590427b882572c81d4e848c": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "fce7a61c25ec4390af43d92b7c473a45": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_30307300bc4e4baf96560e30969a82b6", + "IPY_MODEL_8fc142b628fb40568730234de1cafde2", + "IPY_MODEL_a8464a4c711e4e00aafdfc919b60d07e" + ], + "layout": "IPY_MODEL_5f40db8173dd4d76b6ef5ed6d9ec8b6e" + } + }, + "fdb1941405ed4e4aa06019933892deb3": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + } + } + } + }, + "nbformat": 4, + "nbformat_minor": 0 +}