Training in progress, step 3000
Browse files
.ipynb_checkpoints/fine-tune-whisper-streaming-checkpoint.ipynb
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" Num examples: Unknown\n",
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" Batch size = 16\n",
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"Reading metadata...: 8294it [00:01, 8153.81it/s]\n",
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"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"
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" [2109/5000 6:33:42 < 9:00:12, 0.09 it/s, Epoch 4.01/9223372036854775807]\n",
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" <thead>\n",
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" <th>Step</th>\n",
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" <th>Training Loss</th>\n",
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" <th>Wer</th>\n",
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" <td>1000</td>\n",
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" <td>0.047400</td>\n",
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" <td>0.256107</td>\n",
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" <td>9.461207</td>\n",
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" </tr>\n",
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" <td>2000</td>\n",
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" <td>0.011900</td>\n",
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" <td>0.290058</td>\n",
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" <td>8.972615</td>\n",
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" </tbody>\n",
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"</table><p>"
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" Num examples: Unknown\n",
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" Batch size = 16\n",
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"Reading metadata...: 8294it [00:01, 8153.81it/s]\n",
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"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",
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"Feature extractor saved in ./preprocessor_config.json\n",
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"tokenizer config file saved in ./tokenizer_config.json\n",
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"Special tokens file saved in ./special_tokens_map.json\n",
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"added tokens file saved in ./added_tokens.json\n",
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"Reading metadata...: 16539it [00:00, 56630.09it/s]\n",
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fine-tune-whisper-streaming.ipynb
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" <th>Step</th>\n",
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" <th>Training Loss</th>\n",
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" <th>Validation Loss</th>\n",
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" Num examples: Unknown\n",
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" Batch size = 16\n",
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"Reading metadata...: 8294it [00:01, 8153.81it/s]\n",
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"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"
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" [2297/5000 6:51:48 < 8:05:01, 0.09 it/s, Epoch 4.04/9223372036854775807]\n",
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" <table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <th>Step</th>\n",
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" <th>Training Loss</th>\n",
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" <th>Validation Loss</th>\n",
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" <th>Wer</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tr>\n",
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" <td>1000</td>\n",
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" <td>0.047400</td>\n",
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" <td>0.256107</td>\n",
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" <td>9.461207</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <td>2000</td>\n",
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" <td>0.011900</td>\n",
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" <td>0.290058</td>\n",
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" <td>8.972615</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table><p>"
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],
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" Num examples: Unknown\n",
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" Batch size = 16\n",
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"Reading metadata...: 8294it [00:01, 8153.81it/s]\n",
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+
"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",
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"Feature extractor saved in ./preprocessor_config.json\n",
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+
"tokenizer config file saved in ./tokenizer_config.json\n",
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"Special tokens file saved in ./special_tokens_map.json\n",
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"added tokens file saved in ./added_tokens.json\n",
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"Reading metadata...: 16539it [00:00, 56630.09it/s]\n",
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"Reading metadata...: 8294it [00:00, 44490.77it/s]\n"
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}
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pytorch_model.bin
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runs/Dec07_12-59-07_129-146-180-69/events.out.tfevents.1670417975.129-146-180-69.2248.0
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size 24003
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