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Jateendra
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nlp_bert_emo_classifier

Text Classification
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bert
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update model card README.md

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  1. README.md +17 -17
README.md CHANGED
@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the emotion dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2720
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  ## Model description
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@@ -47,22 +47,22 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 0.9121 | 0.25 | 500 | 0.4423 |
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- | 0.325 | 0.5 | 1000 | 0.3190 |
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- | 0.2594 | 0.75 | 1500 | 0.2662 |
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- | 0.2534 | 1.0 | 2000 | 0.2902 |
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- | 0.1674 | 1.25 | 2500 | 0.2746 |
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- | 0.177 | 1.5 | 3000 | 0.1935 |
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- | 0.1371 | 1.75 | 3500 | 0.2247 |
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- | 0.1734 | 2.0 | 4000 | 0.2031 |
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- | 0.1138 | 2.25 | 4500 | 0.2314 |
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- | 0.1097 | 2.5 | 5000 | 0.2206 |
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- | 0.1171 | 2.75 | 5500 | 0.2538 |
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- | 0.1208 | 3.0 | 6000 | 0.2403 |
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- | 0.0801 | 3.25 | 6500 | 0.2614 |
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- | 0.0736 | 3.5 | 7000 | 0.2699 |
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- | 0.0733 | 3.75 | 7500 | 0.2726 |
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- | 0.071 | 4.0 | 8000 | 0.2720 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the emotion dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2791
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.8887 | 0.25 | 500 | 0.4212 |
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+ | 0.3216 | 0.5 | 1000 | 0.3192 |
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+ | 0.2649 | 0.75 | 1500 | 0.2746 |
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+ | 0.2535 | 1.0 | 2000 | 0.2573 |
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+ | 0.163 | 1.25 | 2500 | 0.2157 |
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+ | 0.1868 | 1.5 | 3000 | 0.2118 |
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+ | 0.1258 | 1.75 | 3500 | 0.2319 |
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+ | 0.1726 | 2.0 | 4000 | 0.1853 |
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+ | 0.1035 | 2.25 | 4500 | 0.2146 |
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+ | 0.1135 | 2.5 | 5000 | 0.2207 |
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+ | 0.1117 | 2.75 | 5500 | 0.2496 |
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+ | 0.1145 | 3.0 | 6000 | 0.2482 |
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+ | 0.0726 | 3.25 | 6500 | 0.2654 |
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+ | 0.0828 | 3.5 | 7000 | 0.2622 |
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+ | 0.0817 | 3.75 | 7500 | 0.2775 |
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+ | 0.0689 | 4.0 | 8000 | 0.2791 |
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  ### Framework versions