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distilbert-base-cased-emotion

Text Classification
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distilbert
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emotion
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update model card README.md

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@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1771
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- - Accuracy: 0.9265
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- - F1: 0.9263
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- - Precision: 0.9276
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- - Recall: 0.9265
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 0.2633 | 1.0 | 500 | 0.2505 | 0.917 | 0.9174 | 0.9183 | 0.917 |
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- | 0.1815 | 2.0 | 1000 | 0.1921 | 0.9305 | 0.9304 | 0.9329 | 0.9305 |
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- | 0.1224 | 3.0 | 1500 | 0.1721 | 0.9355 | 0.9361 | 0.9388 | 0.9355 |
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- | 0.093 | 4.0 | 2000 | 0.1712 | 0.9365 | 0.9359 | 0.9367 | 0.9365 |
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- | 0.0782 | 5.0 | 2500 | 0.2116 | 0.9275 | 0.9271 | 0.9272 | 0.9275 |
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- | 0.0548 | 6.0 | 3000 | 0.2353 | 0.936 | 0.9348 | 0.9362 | 0.936 |
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- | 0.0358 | 7.0 | 3500 | 0.2729 | 0.9325 | 0.9331 | 0.9345 | 0.9325 |
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- | 0.0185 | 8.0 | 4000 | 0.3059 | 0.9325 | 0.9323 | 0.9322 | 0.9325 |
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- | 0.0124 | 9.0 | 4500 | 0.3103 | 0.9325 | 0.9325 | 0.9325 | 0.9325 |
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- | 0.0137 | 10.0 | 5000 | 0.3161 | 0.9305 | 0.9303 | 0.9303 | 0.9305 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3272
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+ - Accuracy: 0.9235
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+ - F1: 0.9217
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+ - Precision: 0.9224
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+ - Recall: 0.9235
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.2776 | 1.0 | 500 | 0.2954 | 0.9 | 0.8957 | 0.9031 | 0.9 |
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+ | 0.1887 | 2.0 | 1000 | 0.1716 | 0.934 | 0.9344 | 0.9370 | 0.934 |
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+ | 0.119 | 3.0 | 1500 | 0.1614 | 0.9345 | 0.9342 | 0.9377 | 0.9345 |
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+ | 0.1001 | 4.0 | 2000 | 0.2018 | 0.936 | 0.9353 | 0.9359 | 0.936 |
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+ | 0.0704 | 5.0 | 2500 | 0.1925 | 0.935 | 0.9349 | 0.9354 | 0.935 |
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+ | 0.0471 | 6.0 | 3000 | 0.2369 | 0.938 | 0.9373 | 0.9377 | 0.938 |
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+ | 0.0322 | 7.0 | 3500 | 0.2693 | 0.938 | 0.9382 | 0.9392 | 0.938 |
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+ | 0.0137 | 8.0 | 4000 | 0.2926 | 0.937 | 0.9371 | 0.9372 | 0.937 |
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+ | 0.0099 | 9.0 | 4500 | 0.2964 | 0.9365 | 0.9362 | 0.9362 | 0.9365 |
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+ | 0.0114 | 10.0 | 5000 | 0.3044 | 0.935 | 0.9349 | 0.9350 | 0.935 |
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  ### Framework versions