Upload Llama2_fineTune.ipynb
Browse files- Llama2_fineTune.ipynb +2217 -0
Llama2_fineTune.ipynb
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|
| 1 |
+
{
|
| 2 |
+
"cells": [
|
| 3 |
+
{
|
| 4 |
+
"cell_type": "code",
|
| 5 |
+
"execution_count": null,
|
| 6 |
+
"metadata": {
|
| 7 |
+
"colab": {
|
| 8 |
+
"base_uri": "https://localhost:8080/"
|
| 9 |
+
},
|
| 10 |
+
"id": "hD8jZmD4pGcP",
|
| 11 |
+
"outputId": "f4b92929-10b7-43e6-c8a6-66cddc81976a"
|
| 12 |
+
},
|
| 13 |
+
"outputs": [
|
| 14 |
+
{
|
| 15 |
+
"name": "stdout",
|
| 16 |
+
"output_type": "stream",
|
| 17 |
+
"text": [
|
| 18 |
+
" Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
|
| 19 |
+
" Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
|
| 20 |
+
" Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
|
| 21 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m155.3/155.3 kB\u001b[0m \u001b[31m3.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 22 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m8.5/8.5 MB\u001b[0m \u001b[31m21.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 23 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m280.0/280.0 kB\u001b[0m \u001b[31m26.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 24 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m510.5/510.5 kB\u001b[0m \u001b[31m32.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 25 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m79.8/79.8 kB\u001b[0m \u001b[31m9.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 26 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m116.3/116.3 kB\u001b[0m \u001b[31m12.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 27 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m134.8/134.8 kB\u001b[0m \u001b[31m15.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 28 |
+
"\u001b[?25h Building wheel for peft (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
|
| 29 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m105.0/105.0 MB\u001b[0m \u001b[31m8.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 30 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m44.6/44.6 kB\u001b[0m \u001b[31m5.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 31 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.2/2.2 MB\u001b[0m \u001b[31m72.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 32 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m195.4/195.4 kB\u001b[0m \u001b[31m20.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 33 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m258.5/258.5 kB\u001b[0m \u001b[31m24.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 34 |
+
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m62.7/62.7 kB\u001b[0m \u001b[31m8.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
| 35 |
+
"\u001b[?25h"
|
| 36 |
+
]
|
| 37 |
+
}
|
| 38 |
+
],
|
| 39 |
+
"source": [
|
| 40 |
+
"!pip install -q -U trl transformers accelerate git+https://github.com/huggingface/peft.git\n",
|
| 41 |
+
"!pip install -q datasets bitsandbytes einops wandb"
|
| 42 |
+
]
|
| 43 |
+
},
|
| 44 |
+
{
|
| 45 |
+
"cell_type": "code",
|
| 46 |
+
"execution_count": null,
|
| 47 |
+
"metadata": {
|
| 48 |
+
"colab": {
|
| 49 |
+
"base_uri": "https://localhost:8080/"
|
| 50 |
+
},
|
| 51 |
+
"id": "rV_jlBYDpXa3",
|
| 52 |
+
"outputId": "4536845b-30f8-46b2-8126-cfdca0303970"
|
| 53 |
+
},
|
| 54 |
+
"outputs": [
|
| 55 |
+
{
|
| 56 |
+
"name": "stdout",
|
| 57 |
+
"output_type": "stream",
|
| 58 |
+
"text": [
|
| 59 |
+
"Requirement already satisfied: datasets in /usr/local/lib/python3.10/dist-packages (2.18.0)\n",
|
| 60 |
+
"Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from datasets) (3.13.1)\n",
|
| 61 |
+
"Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from datasets) (1.25.2)\n",
|
| 62 |
+
"Requirement already satisfied: pyarrow>=12.0.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (14.0.2)\n",
|
| 63 |
+
"Requirement already satisfied: pyarrow-hotfix in /usr/local/lib/python3.10/dist-packages (from datasets) (0.6)\n",
|
| 64 |
+
"Requirement already satisfied: dill<0.3.9,>=0.3.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (0.3.8)\n",
|
| 65 |
+
"Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from datasets) (1.5.3)\n",
|
| 66 |
+
"Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (2.31.0)\n",
|
| 67 |
+
"Requirement already satisfied: tqdm>=4.62.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (4.66.2)\n",
|
| 68 |
+
"Requirement already satisfied: xxhash in /usr/local/lib/python3.10/dist-packages (from datasets) (3.4.1)\n",
|
| 69 |
+
"Requirement already satisfied: multiprocess in /usr/local/lib/python3.10/dist-packages (from datasets) (0.70.16)\n",
|
| 70 |
+
"Requirement already satisfied: fsspec[http]<=2024.2.0,>=2023.1.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (2023.6.0)\n",
|
| 71 |
+
"Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from datasets) (3.9.3)\n",
|
| 72 |
+
"Requirement already satisfied: huggingface-hub>=0.19.4 in /usr/local/lib/python3.10/dist-packages (from datasets) (0.20.3)\n",
|
| 73 |
+
"Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from datasets) (23.2)\n",
|
| 74 |
+
"Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (6.0.1)\n",
|
| 75 |
+
"Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.3.1)\n",
|
| 76 |
+
"Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (23.2.0)\n",
|
| 77 |
+
"Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.4.1)\n",
|
| 78 |
+
"Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (6.0.5)\n",
|
| 79 |
+
"Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.9.4)\n",
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],
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"source": [
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"dataset = load_dataset(\"Open-Orca/OpenOrca\")"
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"[nltk_data] Unzipping tokenizers/punkt.zip.\n"
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"source": [
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"id": "u_sxV48psDal",
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"version_major": 2,
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+
]
|
| 383 |
+
},
|
| 384 |
+
"metadata": {},
|
| 385 |
+
"output_type": "display_data"
|
| 386 |
+
}
|
| 387 |
+
],
|
| 388 |
+
"source": [
|
| 389 |
+
"from nltk.tokenize import word_tokenize\n",
|
| 390 |
+
"\n",
|
| 391 |
+
"import pandas as pd\n",
|
| 392 |
+
"filtered_dataset = dataset['train'].filter(lambda example: len(word_tokenize(example['response'])) >= 100)\n",
|
| 393 |
+
"from sklearn.feature_extraction.text import TfidfVectorizer\n",
|
| 394 |
+
"from sklearn.metrics.pairwise import cosine_similarity\n",
|
| 395 |
+
"vectorizer = TfidfVectorizer(stop_words='english')\n",
|
| 396 |
+
"tfidf_matrix = vectorizer.fit_transform(filtered_dataset['response'])\n",
|
| 397 |
+
"cosine_sim = cosine_similarity(tfidf_matrix, tfidf_matrix)\n",
|
| 398 |
+
"\n",
|
| 399 |
+
"duplicates = set()\n",
|
| 400 |
+
"for i in range(len(cosine_sim)):\n",
|
| 401 |
+
" for j in range(i+1, len(cosine_sim)):\n",
|
| 402 |
+
" if cosine_sim[i][j] > 0.95:\n",
|
| 403 |
+
" duplicates.add(j)\n",
|
| 404 |
+
"\n",
|
| 405 |
+
"dataset_cleaned = dataset.drop(list(duplicates))"
|
| 406 |
+
]
|
| 407 |
+
},
|
| 408 |
+
{
|
| 409 |
+
"cell_type": "code",
|
| 410 |
+
"execution_count": null,
|
| 411 |
+
"metadata": {
|
| 412 |
+
"id": "EE5hsWdOsUQ2"
|
| 413 |
+
},
|
| 414 |
+
"outputs": [],
|
| 415 |
+
"source": [
|
| 416 |
+
"tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)\n",
|
| 417 |
+
"tokenizer.pad_token = tokenizer.eos_token"
|
| 418 |
+
]
|
| 419 |
+
},
|
| 420 |
+
{
|
| 421 |
+
"cell_type": "code",
|
| 422 |
+
"execution_count": null,
|
| 423 |
+
"metadata": {
|
| 424 |
+
"id": "dqbYpot9sOR7"
|
| 425 |
+
},
|
| 426 |
+
"outputs": [],
|
| 427 |
+
"source": [
|
| 428 |
+
"from datasets import load_dataset\n",
|
| 429 |
+
"from transformers import LlamaForMaskedLM, LlamaTokenizer, Trainer, TrainingArguments\n",
|
| 430 |
+
"import torch\n",
|
| 431 |
+
"\n",
|
| 432 |
+
"\n",
|
| 433 |
+
"\n",
|
| 434 |
+
"model_name = \"allenai/llama-large-1B\"\n",
|
| 435 |
+
"model = LlamaForMaskedLM.from_pretrained(model_name)\n",
|
| 436 |
+
"tokenizer = LlamaTokenizer.from_pretrained(model_name)\n",
|
| 437 |
+
"\n",
|
| 438 |
+
"training_args = TrainingArguments(\n",
|
| 439 |
+
" per_device_train_batch_size=4,\n",
|
| 440 |
+
" num_train_epochs=3,\n",
|
| 441 |
+
" logging_dir='./logs',\n",
|
| 442 |
+
")\n",
|
| 443 |
+
"\n",
|
| 444 |
+
"tokenized_dataset = tokenizer(dataset_cleaned['response'].tolist(),\n",
|
| 445 |
+
" padding=True,\n",
|
| 446 |
+
" truncation=True,\n",
|
| 447 |
+
" return_tensors=\"pt\")\n",
|
| 448 |
+
"\n",
|
| 449 |
+
"def preprocess_dataset(dataset):\n",
|
| 450 |
+
" return {\"input_ids\": dataset[\"input_ids\"], \"labels\": dataset[\"input_ids\"]}\n",
|
| 451 |
+
"\n",
|
| 452 |
+
"dataset = tokenized_dataset.map(preprocess_dataset)\n",
|
| 453 |
+
"\n",
|
| 454 |
+
"trainer = Trainer(\n",
|
| 455 |
+
" model=model,\n",
|
| 456 |
+
" args=training_args,\n",
|
| 457 |
+
" train_dataset=dataset,\n",
|
| 458 |
+
")\n",
|
| 459 |
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"\n",
|
| 460 |
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"trainer.train()\n",
|
| 461 |
+
"\n",
|
| 462 |
+
"model.save_pretrained(\"./fine-tuned-llama2\")"
|
| 463 |
+
]
|
| 464 |
+
},
|
| 465 |
+
{
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| 466 |
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"cell_type": "code",
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| 467 |
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"execution_count": null,
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| 468 |
+
"metadata": {
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| 469 |
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"id": "FS0CLr9AtHXf"
|
| 470 |
+
},
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| 471 |
+
"outputs": [],
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| 472 |
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"source": [
|
| 473 |
+
"from huggingface_hub import login\n",
|
| 474 |
+
"login()"
|
| 475 |
+
]
|
| 476 |
+
},
|
| 477 |
+
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| 478 |
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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| 481 |
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"id": "9Cd1ISQqtO97"
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},
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"outputs": [],
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| 485 |
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"model.push_to_hub(\"ocra\")"
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| 486 |
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]
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| 487 |
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}
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],
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"colab": {
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