diff --git a/0-61-llmpr-phi2-sft-model-training.ipynb b/0-61-llmpr-phi2-sft-model-training.ipynb new file mode 100644 index 0000000..1483310 --- /dev/null +++ b/0-61-llmpr-phi2-sft-model-training.ipynb @@ -0,0 +1,1884 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "66a4b2b9", + "metadata": { + "papermill": { + "duration": 0.006214, + "end_time": "2024-04-01T19:47:43.487314", + "exception": false, + "start_time": "2024-04-01T19:47:43.481100", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Phi2 SFT training baseline\n", + "\n", + "## data\n", + "\n", + "use all public data, but I dropped the dupilcate rewrite prompts.\n", + "\n", + "## hyperparamters\n", + "\n", + "epoch: 5\n", + "\n", + "batch size: 2\n", + "\n", + "gradient_accumulation_steps: 8\n", + "\n", + "max_seq_length: 1024\n", + "\n", + "learing rate: 1e-4\n", + "\n", + "\n", + "inference notebook click [here](https://www.kaggle.com/code/mozhiwenmzw/0-61-llmpr-phi2-sft-model-generate-infer?scriptVersionId=169380324)" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "c7d8e020", + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5", + "execution": { + "iopub.execute_input": "2024-04-01T19:47:43.500472Z", + "iopub.status.busy": "2024-04-01T19:47:43.499780Z", + "iopub.status.idle": "2024-04-01T19:48:25.834955Z", + "shell.execute_reply": "2024-04-01T19:48:25.833865Z" + }, + "papermill": { + "duration": 42.344591, + "end_time": "2024-04-01T19:48:25.837728", + "exception": false, + "start_time": "2024-04-01T19:47:43.493137", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "!pip install -Uq /kaggle/input/llm-whls/bitsandbytes-0.41.1-py3-none-any.whl\n", + "!pip install -Uq /kaggle/input/llm-whls/peft-0.4.0-py3-none-any.whl\n", + "!pip install -Uq /kaggle/input/library-off-for-llm/transformers-4.38.2-py3-none-any.whl" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "4b3a3e2e", + "metadata": { + "execution": { + "iopub.execute_input": "2024-04-01T19:48:25.851272Z", + "iopub.status.busy": "2024-04-01T19:48:25.850937Z", + "iopub.status.idle": "2024-04-01T19:48:38.124898Z", + "shell.execute_reply": "2024-04-01T19:48:38.123693Z" + }, + "papermill": { + "duration": 12.283549, + "end_time": "2024-04-01T19:48:38.127430", + "exception": false, + "start_time": "2024-04-01T19:48:25.843881", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "!pip install -Uq /kaggle/input/llm-whls/trl-0.5.0-py3-none-any.whl" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "dcf9c8b1", + "metadata": { + "execution": { + "iopub.execute_input": "2024-04-01T19:48:38.141628Z", + "iopub.status.busy": "2024-04-01T19:48:38.141326Z", + "iopub.status.idle": "2024-04-01T19:48:56.021228Z", + "shell.execute_reply": "2024-04-01T19:48:56.020458Z" + }, + "papermill": { + "duration": 17.889781, + "end_time": "2024-04-01T19:48:56.023449", + "exception": false, + "start_time": "2024-04-01T19:48:38.133668", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-04-01 19:48:48.774314: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "2024-04-01 19:48:48.774409: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "2024-04-01 19:48:48.897909: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "from sklearn.model_selection import train_test_split\n", + "\n", + "from datasets import Dataset\n", + "from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig\n", + "from transformers import TrainingArguments\n", + "\n", + "from trl import SFTTrainer, DataCollatorForCompletionOnlyLM\n", + "from peft import LoraConfig" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "b1b0c135", + "metadata": { + "execution": { + "iopub.execute_input": "2024-04-01T19:48:56.037492Z", + "iopub.status.busy": "2024-04-01T19:48:56.036468Z", + "iopub.status.idle": "2024-04-01T19:48:56.040984Z", + "shell.execute_reply": "2024-04-01T19:48:56.040306Z" + }, + "papermill": { + "duration": 0.013228, + "end_time": "2024-04-01T19:48:56.042824", + "exception": false, + "start_time": "2024-04-01T19:48:56.029596", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "exp_name = 'phi2_public_data_sft'\n", + "data_path = '/kaggle/input/llmpr-public-10k-unique/public_10k_unique_rewrite_prompt.csv'\n", + "model_path = '/kaggle/input/phi/transformers/2/1'\n", + "output_path = f'outputs'\n", + "model_save_path = f'{exp_name}_adapter'" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "60549a25", + "metadata": { + "execution": { + "iopub.execute_input": "2024-04-01T19:48:56.055431Z", + "iopub.status.busy": "2024-04-01T19:48:56.055166Z", + "iopub.status.idle": "2024-04-01T19:48:56.059010Z", + "shell.execute_reply": "2024-04-01T19:48:56.058212Z" + }, + "papermill": { + "duration": 0.012302, + "end_time": "2024-04-01T19:48:56.060945", + "exception": false, + "start_time": "2024-04-01T19:48:56.048643", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "epochs=5\n", + "batch_size=1 # 2 \n", + "max_seq_length=512 # 1024 \n", + "lr = 1e-4" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "102f68d1", + "metadata": { + "execution": { + "iopub.execute_input": "2024-04-01T19:48:56.073684Z", + "iopub.status.busy": "2024-04-01T19:48:56.073430Z", + "iopub.status.idle": "2024-04-01T19:48:56.758366Z", + "shell.execute_reply": "2024-04-01T19:48:56.757500Z" + }, + "papermill": { + "duration": 0.693865, + "end_time": "2024-04-01T19:48:56.760700", + "exception": false, + "start_time": "2024-04-01T19:48:56.066835", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "df = pd.read_csv(data_path)\n", + "train_df, val_df = train_test_split(df, test_size=0.3, random_state=42)\n", + "train_df = train_df.reset_index(drop=True)\n", + "val_df = val_df.reset_index(drop=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "8f7ee657", + "metadata": { + "execution": { + "iopub.execute_input": "2024-04-01T19:48:56.775047Z", + "iopub.status.busy": "2024-04-01T19:48:56.774760Z", + "iopub.status.idle": "2024-04-01T19:48:56.855008Z", + "shell.execute_reply": "2024-04-01T19:48:56.854244Z" + }, + "papermill": { + "duration": 0.090513, + "end_time": "2024-04-01T19:48:56.857308", + "exception": false, + "start_time": "2024-04-01T19:48:56.766795", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "train_ds = Dataset.from_pandas(train_df)\n", + "val_ds = Dataset.from_pandas(val_df)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "d8378019", + "metadata": { + "execution": { + "iopub.execute_input": "2024-04-01T19:48:56.870624Z", + "iopub.status.busy": "2024-04-01T19:48:56.870337Z", + "iopub.status.idle": "2024-04-01T19:48:57.049407Z", + "shell.execute_reply": "2024-04-01T19:48:57.048525Z" + }, + "papermill": { + "duration": 0.18791, + "end_time": "2024-04-01T19:48:57.051364", + "exception": false, + "start_time": "2024-04-01T19:48:56.863454", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n" + ] + } + ], + "source": [ + "tokenizer = AutoTokenizer.from_pretrained(\n", + " model_path,\n", + " )\n", + "tokenizer.pad_token = tokenizer.eos_token" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "b91cd8a5", + "metadata": { + "execution": { + "iopub.execute_input": "2024-04-01T19:48:57.064721Z", + "iopub.status.busy": "2024-04-01T19:48:57.064444Z", + "iopub.status.idle": "2024-04-01T19:48:57.069894Z", + "shell.execute_reply": "2024-04-01T19:48:57.069255Z" + }, + "papermill": { + "duration": 0.014206, + "end_time": "2024-04-01T19:48:57.071739", + "exception": false, + "start_time": "2024-04-01T19:48:57.057533", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "bnb_config = BitsAndBytesConfig(\n", + " load_in_4bit=True,\n", + " bnb_4bit_quant_type='nf4',\n", + " bnb_4bit_compute_dtype='float16',\n", + " bnb_4bit_use_double_quant=False,\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "2eb64b29", + "metadata": { + "execution": { + "iopub.execute_input": "2024-04-01T19:48:57.084486Z", + "iopub.status.busy": "2024-04-01T19:48:57.084243Z", + "iopub.status.idle": "2024-04-01T19:50:03.579414Z", + "shell.execute_reply": "2024-04-01T19:50:03.578411Z" + }, + "papermill": { + "duration": 66.503944, + "end_time": "2024-04-01T19:50:03.581517", + "exception": false, + "start_time": "2024-04-01T19:48:57.077573", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/conda/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py:466: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.\n", + " warnings.warn(\n", + "`low_cpu_mem_usage` was None, now set to True since model is quantized.\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "fe785780e5134d68bac28f82385c9c9c", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Loading checkpoint shards: 0%| | 0/2 [00:00=0.41.3` installed.\n" + ] + } + ], + "source": [ + "model = AutoModelForCausalLM.from_pretrained(model_path,\n", + " quantization_config=bnb_config,\n", + " trust_remote_code=True,\n", + " use_auth_token=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "5f00b698", + "metadata": { + "execution": { + "iopub.execute_input": "2024-04-01T19:50:03.595638Z", + "iopub.status.busy": "2024-04-01T19:50:03.595350Z", + "iopub.status.idle": "2024-04-01T19:50:03.599672Z", + "shell.execute_reply": "2024-04-01T19:50:03.598754Z" + }, + "papermill": { + "duration": 0.013614, + "end_time": "2024-04-01T19:50:03.601762", + "exception": false, + "start_time": "2024-04-01T19:50:03.588148", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "model.config.gradient_checkpointing = False" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "3def3247", + "metadata": { + "execution": { + "iopub.execute_input": "2024-04-01T19:50:03.615840Z", + "iopub.status.busy": "2024-04-01T19:50:03.615259Z", + "iopub.status.idle": "2024-04-01T19:50:03.620254Z", + "shell.execute_reply": "2024-04-01T19:50:03.619436Z" + }, + "papermill": { + "duration": 0.014233, + "end_time": "2024-04-01T19:50:03.622191", + "exception": false, + "start_time": "2024-04-01T19:50:03.607958", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "def token_len(text):\n", + " tokenized = tokenizer(text, return_length=True)\n", + " length = tokenized['length'][0]\n", + " return length" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "07b07ead", + "metadata": { + "execution": { + "iopub.execute_input": "2024-04-01T19:50:03.635805Z", + "iopub.status.busy": "2024-04-01T19:50:03.635491Z", + "iopub.status.idle": "2024-04-01T19:50:03.642243Z", + "shell.execute_reply": "2024-04-01T19:50:03.641421Z" + }, + "papermill": { + "duration": 0.015899, + "end_time": "2024-04-01T19:50:03.644248", + "exception": false, + "start_time": "2024-04-01T19:50:03.628349", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "def formatting_prompts_func(example):\n", + " output_texts = []\n", + " for i in range(len(example['rewritten_text'])):\n", + " ori_text = example['original_text'][i]\n", + " rew_text = example['rewritten_text'][i]\n", + " rew_prompt = example['rewrite_prompt'][i]\n", + " text = f\"Instruct: Original Text:{ori_text}\\nRewritten Text:{rew_text}\\nWrite a prompt that was likely given to the LLM to rewrite original text into rewritten text.Output: {rew_prompt}\"\n", + " if token_len(text) > max_seq_length:\n", + " continue\n", + " output_texts.append(text)\n", + " return output_texts" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "3dd154d4", + "metadata": { + "execution": { + "iopub.execute_input": "2024-04-01T19:50:03.658166Z", + "iopub.status.busy": "2024-04-01T19:50:03.657534Z", + "iopub.status.idle": "2024-04-01T19:50:03.665570Z", + "shell.execute_reply": "2024-04-01T19:50:03.664243Z" + }, + "papermill": { + "duration": 0.01869, + "end_time": "2024-04-01T19:50:03.669126", + "exception": false, + "start_time": "2024-04-01T19:50:03.650436", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "response_template = \"Output:\"\n", + "collator = DataCollatorForCompletionOnlyLM(response_template=response_template, \n", + " tokenizer=tokenizer)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "ccb460cf", + "metadata": { + "execution": { + "iopub.execute_input": "2024-04-01T19:50:03.683251Z", + "iopub.status.busy": "2024-04-01T19:50:03.682609Z", + "iopub.status.idle": "2024-04-01T19:50:03.687642Z", + "shell.execute_reply": "2024-04-01T19:50:03.686816Z" + }, + "papermill": { + "duration": 0.014422, + "end_time": "2024-04-01T19:50:03.689791", + "exception": false, + "start_time": "2024-04-01T19:50:03.675369", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "peft_config = LoraConfig(\n", + " r=16,\n", + " lora_alpha=32,\n", + " lora_dropout=0.05,\n", + " bias=\"none\",\n", + " task_type=\"CAUSAL_LM\",\n", + " target_modules= [\"q_proj\", \"k_proj\", \"v_proj\", \"dense\"],\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "f1d06270", + "metadata": { + "execution": { + "iopub.execute_input": "2024-04-01T19:50:03.703462Z", + "iopub.status.busy": "2024-04-01T19:50:03.703125Z", + "iopub.status.idle": "2024-04-01T19:50:03.711113Z", + "shell.execute_reply": "2024-04-01T19:50:03.710346Z" + }, + "papermill": { + "duration": 0.016922, + "end_time": "2024-04-01T19:50:03.713013", + "exception": false, + "start_time": "2024-04-01T19:50:03.696091", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "args = TrainingArguments(\n", + " output_dir = output_path,\n", + " fp16=True,\n", + " learning_rate=lr,\n", + " optim=\"adafactor\",\n", + " num_train_epochs=epochs,\n", + " per_device_train_batch_size=batch_size,\n", + " per_device_eval_batch_size=batch_size*2,\n", + " gradient_accumulation_steps=8,\n", + " evaluation_strategy=\"epoch\",\n", + " save_strategy=\"epoch\",\n", + " save_total_limit=1,\n", + " logging_steps=50,\n", + " lr_scheduler_type=\"cosine\",\n", + " warmup_ratio=0.1,\n", + " weight_decay=0.01,\n", + " report_to='none',\n", + " load_best_model_at_end=True,\n", + " metric_for_best_model=\"eval_loss\",\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "159eb171", + "metadata": { + "execution": { + "iopub.execute_input": "2024-04-01T19:50:03.726471Z", + "iopub.status.busy": "2024-04-01T19:50:03.726184Z", + "iopub.status.idle": "2024-04-01T19:50:41.360429Z", + "shell.execute_reply": "2024-04-01T19:50:41.359313Z" + }, + "papermill": { + "duration": 37.643457, + "end_time": "2024-04-01T19:50:41.362588", + "exception": false, + "start_time": "2024-04-01T19:50:03.719131", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/conda/lib/python3.10/site-packages/peft/utils/other.py:102: FutureWarning: prepare_model_for_int8_training is deprecated and will be removed in a future version. Use prepare_model_for_kbit_training instead.\n", + " warnings.warn(\n", + "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "36f91f33376d428280c3132bbc521d98", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0/8 [00:00 2048). Running this sequence through the model will result in indexing errors\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "84b53eb01f954e838cf7721223a5e4f5", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0/4 [00:00\n", + " \n", + " \n", + " [2640/2640 8:48:49, Epoch 4/5]\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
EpochTraining LossValidation Loss
01.1721001.096457
11.0161000.979691
20.8616000.930683
30.7785000.920767
40.8229000.917286

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