Training in progress, step 4000

fine-tune-whisper-streaming.ipynb

@@ -875,8 +875,8 @@
        "\n",
        "    <div>\n",
        "      \n",
-       "      <progress value='3001' max='5000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
-       "      [3001/5000 3:46:27 < 2:30:56, 0.22 it/s, Epoch 18.01/9223372036854775807]\n",
+       "      <progress value='4001' max='5000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      [4001/5000 5:08:08 < 1:16:58, 0.22 it/s, Epoch 24.02/9223372036854775807]\n",
        "    </div>\n",
        "    <table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
@@ -900,6 +900,12 @@
        "      <td>0.512787</td>\n",
        "      <td>35.974908</td>\n",
        "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3000</td>\n",
+       "      <td>0.000800</td>\n",
+       "      <td>0.545756</td>\n",
+       "      <td>35.784333</td>\n",
+       "    </tr>\n",
        "  </tbody>\n",
        "</table><p>"
       ],
@@ -968,6 +974,28 @@
       "  Num examples: Unknown\n",
       "  Batch size = 8\n",
       "Reading metadata...: 3749it [00:00, 28834.15it/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",
+      "Saving model checkpoint to ./checkpoint-3000\n",
+      "Configuration saved in ./checkpoint-3000/config.json\n",
+      "Model weights saved in ./checkpoint-3000/pytorch_model.bin\n",
+      "Feature extractor saved in ./checkpoint-3000/preprocessor_config.json\n",
+      "tokenizer config file saved in ./checkpoint-3000/tokenizer_config.json\n",
+      "Special tokens file saved in ./checkpoint-3000/special_tokens_map.json\n",
+      "added tokens file saved in ./checkpoint-3000/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",
+      "Reading metadata...: 5194it [00:00, 24644.13it/s]\n",
+      "Reading metadata...: 5194it [00:00, 10820.40it/s]\n",
+      "Reading metadata...: 5194it [00:00, 30318.60it/s]\n",
+      "Reading metadata...: 5194it [00:00, 28565.08it/s]\n",
+      "Reading metadata...: 5194it [00:00, 24580.04it/s]\n",
+      "Reading metadata...: 5194it [00:00, 30543.46it/s]\n",
+      "***** Running Evaluation *****\n",
+      "  Num examples: Unknown\n",
+      "  Batch size = 8\n",
+      "Reading metadata...: 3749it [00:00, 24211.98it/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"
      ]
     }
@@ -1007,7 +1035,7 @@
     "    \"dataset_tags\": \"mozilla-foundation/common_voice_11_0\",\n",
     "    \"dataset\": \"Common Voice 11.0\",  # a 'pretty' name for the training dataset\n",
     "    \"language\": \"lt\",\n",
-    "    \"model_name\": \"Whisper Small Lt and Sr\",  # a 'pretty' name for your model\n",
+    "    \"model_name\": \"Whisper Small Lt\",  # a 'pretty' name for your model\n",
     "    \"finetuned_from\": \"openai/whisper-small\",\n",
     "    \"tasks\": \"automatic-speech-recognition\",\n",
     "    \"tags\": \"whisper-event\",\n",

pytorch_model.bin

@@ -1,3 +1,3 @@
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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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+size 30664