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change base to large

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s487194 2024-02-01 03:10:09 +01:00
parent b9f590cf3f
commit 5412489296
1 changed files with 52 additions and 52 deletions
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104
T5_encoder_decoder.ipynb → T5_encoder_decoder-large.ipynb
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@ -16,7 +16,7 @@
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@ -480,7 +480,7 @@
{ {
"cell_type": "code", "cell_type": "code",
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"model_name = \"t5-base\"\n", "model_name = \"t5-large\"\n",
"tokenizer = AutoTokenizer.from_pretrained(model_name, model_max_length = 128)\n", "tokenizer = AutoTokenizer.from_pretrained(model_name, model_max_length = 128)\n",
"\n", "\n",
"def tokenize_function(examples):\n", "def tokenize_function(examples):\n",
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@ -548,7 +548,7 @@
"output_type": "stream", "output_type": "stream",
"name": "stderr", "name": "stderr",
"text": [ "text": [
"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", "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",
"You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n" "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
] ]
} }
@ -572,19 +572,19 @@
"metadata": { "metadata": {
"id": "hpRwZ0QhrV92" "id": "hpRwZ0QhrV92"
}, },
"execution_count": 44, "execution_count": 6,
"outputs": [] "outputs": []
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{ {
"cell_type": "code", "cell_type": "code",
"source": [ "source": [
"train_arguments = TrainingArguments(num_train_epochs=1, per_device_train_batch_size=32, output_dir=\"./Output\", evaluation_strategy=\"epoch\",)\n", "train_arguments = TrainingArguments(num_train_epochs=1, per_device_train_batch_size=8, output_dir=\"./Output\", evaluation_strategy=\"epoch\",)\n",
"trainer=Trainer(model=model, args=train_arguments, train_dataset=tokenized_dataset_train, eval_dataset=tokenized_dataset_eval, compute_metrics=compute_metrics)" "trainer=Trainer(model=model, args=train_arguments, train_dataset=tokenized_dataset_train, eval_dataset=tokenized_dataset_eval, compute_metrics=compute_metrics)"
], ],
"metadata": { "metadata": {
"id": "P4hpYtvHbRex" "id": "P4hpYtvHbRex"
}, },
"execution_count": 45, "execution_count": 11,
"outputs": [] "outputs": []
}, },
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@ -598,9 +598,9 @@
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"height": 141 "height": 141
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"execution_count": 46, "execution_count": 12,
"outputs": [ "outputs": [
{ {
"output_type": "display_data", "output_type": "display_data",
@ -612,8 +612,8 @@
"\n", "\n",
" <div>\n", " <div>\n",
" \n", " \n",
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" [158/158 04:34, Epoch 1/1]\n", " [632/632 18:44, Epoch 1/1]\n",
" </div>\n", " </div>\n",
" <table border=\"1\" class=\"dataframe\">\n", " <table border=\"1\" class=\"dataframe\">\n",
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@ -627,9 +627,9 @@
" <tbody>\n", " <tbody>\n",
" <tr>\n", " <tr>\n",
" <td>1</td>\n", " <td>1</td>\n",
" <td>No log</td>\n", " <td>0.453600</td>\n",
" <td>1.616516</td>\n", " <td>0.352671</td>\n",
" <td>0.888672</td>\n", " <td>0.904297</td>\n",
" </tr>\n", " </tr>\n",
" </tbody>\n", " </tbody>\n",
"</table><p>" "</table><p>"
@ -641,11 +641,11 @@
"output_type": "execute_result", "output_type": "execute_result",
"data": { "data": {
"text/plain": [ "text/plain": [
"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})" "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})"
] ]
}, },
"metadata": {}, "metadata": {},
"execution_count": 46 "execution_count": 12
} }
] ]
} }