trial-fune-tune-book.ipynb

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   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "The cache for model files in Transformers v4.22.0 has been updated. Migrating your old cache. This is a one-time only operation. You can interrupt this and resume the migration later on by calling `transformers.utils.move_cache()`.\n",
      "0it [00:00, ?it/s]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "DatasetDict({\n",
       "    train: Dataset({\n",
       "        features: ['label', 'text'],\n",
       "        num_rows: 1000\n",
       "    })\n",
       "    validation: Dataset({\n",
       "        features: ['label', 'text'],\n",
       "        num_rows: 1000\n",
       "    })\n",
       "})"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from datasets import load_dataset, DatasetDict, Dataset\n",
    "\n",
    "from transformers import (\n",
    "    AutoTokenizer,\n",
    "    AutoConfig, \n",
    "    AutoModelForSequenceClassification,\n",
    "    DataCollatorWithPadding,\n",
    "    TrainingArguments,\n",
    "    Trainer)\n",
    "\n",
    "from peft import PeftModel, PeftConfig, get_peft_model, LoraConfig\n",
    "import evaluate\n",
    "import torch\n",
    "import numpy as np\n",
    "dataset = load_dataset('shawhin/imdb-truncated')\n",
    "dataset\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(0.5)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array(dataset['train']['label']).sum()/len(dataset['train']['label'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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