End of training

fine-tune-whisper-streaming.ipynb

@@ -847,7 +847,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "id": "ee8b7b8e-1c9a-4d77-9137-1778a629e6de",
    "metadata": {},
    "outputs": [
@@ -875,8 +875,8 @@
        "\n",
        "    <div>\n",
        "      \n",
-       "      <progress value='5001' max='5000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
-       "      [5000/5000 6:31:22, Epoch 30.02/9223372036854775807]\n",
+       "      <progress value='5000' max='5000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      [5000/5000 6:53:14, Epoch 30/9223372036854775807]\n",
        "    </div>\n",
        "    <table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
@@ -912,6 +912,12 @@
        "      <td>0.565175</td>\n",
        "      <td>35.824036</td>\n",
        "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5000</td>\n",
+       "      <td>0.000400</td>\n",
+       "      <td>0.572376</td>\n",
+       "      <td>35.859769</td>\n",
+       "    </tr>\n",
        "  </tbody>\n",
        "</table><p>"
       ],
@@ -1024,8 +1030,35 @@
       "  Num examples: Unknown\n",
       "  Batch size = 8\n",
       "Reading metadata...: 3749it [00:00, 4607.71it/s]\n",
-      "The following columns in the evaluation set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: input_length. If input_length are not expected by `WhisperForConditionalGeneration.forward`,  you can safely ignore this message.\n"
+      "The following columns in the evaluation set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: input_length. If input_length are not expected by `WhisperForConditionalGeneration.forward`,  you can safely ignore this message.\n",
+      "Saving model checkpoint to ./checkpoint-5000\n",
+      "Configuration saved in ./checkpoint-5000/config.json\n",
+      "Model weights saved in ./checkpoint-5000/pytorch_model.bin\n",
+      "Feature extractor saved in ./checkpoint-5000/preprocessor_config.json\n",
+      "tokenizer config file saved in ./checkpoint-5000/tokenizer_config.json\n",
+      "Special tokens file saved in ./checkpoint-5000/special_tokens_map.json\n",
+      "added tokens file saved in ./checkpoint-5000/added_tokens.json\n",
+      "Feature extractor saved in ./preprocessor_config.json\n",
+      "tokenizer config file saved in ./tokenizer_config.json\n",
+      "Special tokens file saved in ./special_tokens_map.json\n",
+      "added tokens file saved in ./added_tokens.json\n",
+      "\n",
+      "\n",
+      "Training completed. Do not forget to share your model on huggingface.co/models =)\n",
+      "\n",
+      "\n",
+      "Loading best model from ./checkpoint-3000 (score: 35.78433318775559).\n"
      ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "TrainOutput(global_step=5000, training_loss=0.11304525989443064, metrics={'train_runtime': 24832.6385, 'train_samples_per_second': 6.443, 'train_steps_per_second': 0.201, 'total_flos': 4.59831976869888e+19, 'train_loss': 0.11304525989443064, 'epoch': 30.02})"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [

pytorch_model.bin

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runs/Dec14_09-49-59_129-146-98-164/events.out.tfevents.1671011416.129-146-98-164.123311.0

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