change base to large
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b9f590cf3f
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5412489296
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@ -459,7 +459,7 @@
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"execution_count": 3,
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@ -480,7 +480,7 @@
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{
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"cell_type": "code",
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"source": [
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"model_name = \"t5-base\"\n",
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"model_name = \"t5-large\"\n",
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"tokenizer = AutoTokenizer.from_pretrained(model_name, model_max_length = 128)\n",
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"\n",
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"def tokenize_function(examples):\n",
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"execution_count": 4,
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@ -522,7 +522,7 @@
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@ -540,7 +540,7 @@
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"execution_count": 5,
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"outputs": [
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@ -548,7 +548,7 @@
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"output_type": "stream",
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"name": "stderr",
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"text": [
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"Some weights of T5ForSequenceClassification were not initialized from the model checkpoint at t5-base and are newly initialized: ['classification_head.out_proj.bias', 'classification_head.out_proj.weight', 'classification_head.dense.weight', 'classification_head.dense.bias']\n",
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"Some weights of T5ForSequenceClassification were not initialized from the model checkpoint at t5-large and are newly initialized: ['classification_head.out_proj.weight', 'classification_head.dense.bias', 'classification_head.dense.weight', 'classification_head.out_proj.bias']\n",
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"You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
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]
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}
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@ -572,19 +572,19 @@
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"metadata": {
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"id": "hpRwZ0QhrV92"
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},
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"execution_count": 44,
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"execution_count": 6,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"train_arguments = TrainingArguments(num_train_epochs=1, per_device_train_batch_size=32, output_dir=\"./Output\", evaluation_strategy=\"epoch\",)\n",
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"train_arguments = TrainingArguments(num_train_epochs=1, per_device_train_batch_size=8, output_dir=\"./Output\", evaluation_strategy=\"epoch\",)\n",
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"trainer=Trainer(model=model, args=train_arguments, train_dataset=tokenized_dataset_train, eval_dataset=tokenized_dataset_eval, compute_metrics=compute_metrics)"
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],
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"metadata": {
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"id": "P4hpYtvHbRex"
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},
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"execution_count": 45,
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"execution_count": 11,
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"outputs": []
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},
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{
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@ -598,9 +598,9 @@
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"base_uri": "https://localhost:8080/",
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"height": 141
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},
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"outputId": "ed0f490c-f168-4382-8211-c05ee12be011"
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"outputId": "7ec665e1-1db5-49ee-a482-13ca53836418"
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},
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"execution_count": 46,
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"execution_count": 12,
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"outputs": [
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{
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"output_type": "display_data",
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"\n",
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" <div>\n",
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" \n",
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" <progress value='158' max='158' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
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" [158/158 04:34, Epoch 1/1]\n",
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" <progress value='632' max='632' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
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" [632/632 18:44, Epoch 1/1]\n",
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" </div>\n",
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" <table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <td>1</td>\n",
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" <td>No log</td>\n",
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" <td>1.616516</td>\n",
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" <td>0.888672</td>\n",
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" <td>0.453600</td>\n",
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" <td>0.352671</td>\n",
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" <td>0.904297</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table><p>"
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"output_type": "execute_result",
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"data": {
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"text/plain": [
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"TrainOutput(global_step=158, training_loss=0.03489681135250043, metrics={'train_runtime': 276.2183, 'train_samples_per_second': 18.29, 'train_steps_per_second': 0.572, 'total_flos': 771417209622528.0, 'train_loss': 0.03489681135250043, 'epoch': 1.0})"
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"TrainOutput(global_step=632, training_loss=0.4112016822718367, metrics={'train_runtime': 1126.6685, 'train_samples_per_second': 4.484, 'train_steps_per_second': 0.561, 'total_flos': 2738543023411200.0, 'train_loss': 0.4112016822718367, 'epoch': 1.0})"
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]
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},
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"metadata": {},
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"execution_count": 46
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"execution_count": 12
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}
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]
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}
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