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update model card README.md

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@@ -20,10 +20,10 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.926
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  - name: F1
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  type: f1
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- value: 0.9258424592458041
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,9 +33,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2185
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- - Accuracy: 0.926
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- - F1: 0.9258
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  ## Model description
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@@ -66,13 +66,13 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 0.8082 | 1.0 | 250 | 0.3139 | 0.9095 | 0.9073 |
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- | 0.2492 | 2.0 | 500 | 0.2185 | 0.926 | 0.9258 |
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  ### Framework versions
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- - Transformers 4.13.0
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  - Pytorch 1.12.1+cu113
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  - Datasets 1.16.1
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  - Tokenizers 0.10.3
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.923
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  - name: F1
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  type: f1
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+ value: 0.9230800058707119
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2188
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+ - Accuracy: 0.923
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+ - F1: 0.9231
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.8234 | 1.0 | 250 | 0.3123 | 0.9075 | 0.9058 |
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+ | 0.2493 | 2.0 | 500 | 0.2188 | 0.923 | 0.9231 |
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  ### Framework versions
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+ - Transformers 4.11.3
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  - Pytorch 1.12.1+cu113
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  - Datasets 1.16.1
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  - Tokenizers 0.10.3