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update model card README.md

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  license: apache-2.0
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  tags:
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  - generated_from_trainer
 
 
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  metrics:
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  - accuracy
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  - f1
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  model-index:
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  - name: distilbert-base-uncased-finetuned-emotion
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- results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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
@@ -15,11 +33,11 @@ should probably proofread and complete it, then remove this comment. -->
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  # distilbert-base-uncased-finetuned-emotion
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- This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2180
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- - Accuracy: 0.924
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- - F1: 0.9240
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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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- | 0.8166 | 1.0 | 250 | 0.3218 | 0.903 | 0.8983 |
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- | 0.2514 | 2.0 | 500 | 0.2180 | 0.924 | 0.9240 |
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  ### Framework versions
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- - Transformers 4.26.1
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- - Pytorch 1.13.1+cu116
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- - Datasets 2.10.1
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- - Tokenizers 0.13.2
 
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  license: apache-2.0
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  tags:
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  - generated_from_trainer
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+ datasets:
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+ - emotion
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  metrics:
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  - accuracy
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  - f1
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  model-index:
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  - name: distilbert-base-uncased-finetuned-emotion
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: emotion
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+ type: emotion
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+ config: split
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+ split: validation
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+ args: split
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9235
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+ - name: F1
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+ type: f1
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+ value: 0.9232723220041145
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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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  # distilbert-base-uncased-finetuned-emotion
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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: 0.2245
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+ - Accuracy: 0.9235
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+ - F1: 0.9233
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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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+ | 0.8066 | 1.0 | 250 | 0.3253 | 0.8985 | 0.8934 |
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+ | 0.2539 | 2.0 | 500 | 0.2245 | 0.9235 | 0.9233 |
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  ### Framework versions
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+ - Transformers 4.29.2
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.3