{
 "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",
      "🦥 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<?, ?it/s]--------\n",
      "step 1: Old耿举枪，斜着眼睛眯起来，扣动扳机，砰的一声响，子弹一颗颗落在地上，像是打在棉花团上一样，砰的一声又一声，声音很清脆。<|im_end|>\n",
      "--------\n",
      "step 2: Old耿举枪，斜着眼睛眯起来，扣动扳机，砰的一声响，子弹一颗颗落在地上，像是打在棉花团上一样，砰的一声又一声，声音很清脆。\n",
      "--------\n",
      "step 3: Old耿举枪，斜着眼睛眯起来，扣动扳机，砰的一声响，子弹一颗颗落在地上，像是打在棉花团上一样，砰的一声又一声，声音很清脆。\n",
      "100%|███████████████████████████████████████| 1133/1133 [21:27<00:00,  1.14s/it]\n",
      "                                             chinese  ...                        unsloth/Qwen2-0.5B-Instruct\n",
      "0  老耿端起枪，眯缝起一只三角眼，一搂扳机响了枪，冰雹般的金麻雀劈哩啪啦往下落，铁砂子在柳枝间飞...  ...  Old耿举枪，斜着眼睛眯起来，扣动扳机，砰的一声响，子弹一颗颗落在地上，像是打在棉花团上一样...\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 🤗 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%|████████████| 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",
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      "{'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%|█████████████████████████████████████| 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<?, ?it/s]--------\n",
      "step 1: 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.<|im_end|>\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%|███████████████████████████████████████| 1133/1133 [29:54<00:00,  1.58s/it]\n",
      "                                             chinese  ...             unsloth/Qwen2-0.5B-Instruct(finetuned)\n",
      "0  老耿端起枪，眯缝起一只三角眼，一搂扳机响了枪，冰雹般的金麻雀劈哩啪啦往下落，铁砂子在柳枝间飞...  ...  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%|█████████████████████| 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%|███████████████████████████████| 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",
      "🦥 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%|████████████████████████| 4528/4528 [00:00<00:00, 31812.02 examples/s]\n",
      "Map: 100%|████████████████████████| 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<?, ?it/s]--------\n",
      "step 1: 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.<|im_end|>\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%|█████████████████████████████████████| 1133/1133 [1:34:06<00:00,  4.98s/it]\n",
      "                                             chinese  ...                        unsloth/Qwen2-1.5B-Instruct\n",
      "0  老耿端起枪，眯缝起一只三角眼，一搂扳机响了枪，冰雹般的金麻雀劈哩啪啦往下落，铁砂子在柳枝间飞...  ...  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 🤗 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%|████████████| 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",
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      "{'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%|█████████████████████████████████████| 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<?, ?it/s]--------\n",
      "step 1: 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.<|im_end|>\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%|█████████████████████████████████████| 1133/1133 [2:11:15<00:00,  6.95s/it]\n",
      "                                             chinese  ...             unsloth/Qwen2-1.5B-Instruct(finetuned)\n",
      "0  老耿端起枪，眯缝起一只三角眼，一搂扳机响了枪，冰雹般的金麻雀劈哩啪啦往下落，铁砂子在柳枝间飞...  ...  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%|███████████████████| 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%|███████████████████████████████| 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",
      "🦥 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%|████████████████████████| 4528/4528 [00:00<00:00, 12373.02 examples/s]\n",
      "Map: 100%|█████████████████████████| 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<?, ?it/s]--------\n",
      "step 1: 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.<|im_end|>\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%|█████████████████████████████████████| 1133/1133 [1:20:24<00:00,  4.26s/it]\n",
      "                                             chinese  ...               unsloth/Qwen2-0.5B-Instruct-bnb-4bit\n",
      "0  老耿端起枪，眯缝起一只三角眼，一搂扳机响了枪，冰雹般的金麻雀劈哩啪啦往下落，铁砂子在柳枝间飞...  ...  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 🤗 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%|████████████| 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",
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      "{'loss': 1.715, 'grad_norm': 0.7505761384963989, 'learning_rate': 0.00018603006189213086, 'epoch': 0.71}\n",
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      "{'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%|█████████████████████████████████████| 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<?, ?it/s]--------\n",
      "step 1: 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 of钢铁的碎块) that fell powerfully in the willows between them.<|im_end|>\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 of钢铁的碎块) 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 of钢铁的碎块) that fell powerfully in the willows between them.\n",
      "100%|█████████████████████████████████████| 1133/1133 [1:48:52<00:00,  5.77s/it]\n",
      "                                             chinese  ...    unsloth/Qwen2-0.5B-Instruct-bnb-4bit(finetuned)\n",
      "0  老耿端起枪，眯缝起一只三角眼，一搂扳机响了枪，冰雹般的金麻雀劈哩啪啦往下落，铁砂子在柳枝间飞...  ...  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%|█████████████████████| 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%|███████████████████████████████| 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",
      "🦥 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%|████████████████████████| 4528/4528 [00:00<00:00, 10965.65 examples/s]\n",
      "Map: 100%|█████████████████████████| 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<?, ?it/s]--------\n",
      "step 1: Old耿拿起枪，眯缝起一只三角眼，一搂扳机响了枪，冰雹般的金麻雀劈哩啪啦往下落，铁砂子在柳枝间飞迸着，嚓嚓有声。<|im_end|>\n",
      "--------\n",
      "step 2: Old耿拿起枪，眯缝起一只三角眼，一搂扳机响了枪，冰雹般的金麻雀劈哩啪啦往下落，铁砂子在柳枝间飞迸着，嚓嚓有声。\n",
      "--------\n",
      "step 3: Old耿拿起枪，眯缝起一只三角眼，一搂扳机响了枪，冰雹般的金麻雀劈哩啪啦往下落，铁砂子在柳枝间飞迸着，嚓嚓有声。\n",
      "100%|█████████████████████████████████████| 1133/1133 [1:09:28<00:00,  3.68s/it]\n",
      "                                             chinese  ...               unsloth/Qwen2-1.5B-Instruct-bnb-4bit\n",
      "0  老耿端起枪，眯缝起一只三角眼，一搂扳机响了枪，冰雹般的金麻雀劈哩啪啦往下落，铁砂子在柳枝间飞...  ...  Old耿拿起枪，眯缝起一只三角眼，一搂扳机响了枪，冰雹般的金麻雀劈哩啪啦往下落，铁砂子在柳枝...\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 🤗 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%|████████████| 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",
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      "100%|█████████████████████████████████████| 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<?, ?it/s]--------\n",
      "step 1: Old Geng raised his pistol, cocked it, and fired – a string of pocky-gun shots sent the shooting birds skittering to the ground.<|im_end|>\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%|█████████████████████████████████████| 1133/1133 [1:44:47<00:00,  5.55s/it]\n",
      "                                             chinese  ...    unsloth/Qwen2-1.5B-Instruct-bnb-4bit(finetuned)\n",
      "0  老耿端起枪，眯缝起一只三角眼，一搂扳机响了枪，冰雹般的金麻雀劈哩啪啦往下落，铁砂子在柳枝间飞...  ...  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%|███████████████████| 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%|███████████████████████████████| 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"
     ]
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   ],
   "source": [
    "%%time\n",
    "\n",
    "!./scripts/tune-small.sh"
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