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DistilBERTFINAL_ctxSentence_TRAIN_all_TEST_NULL_second_train_set_null_False

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update model card README.md

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  ---
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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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  # DistilBERTFINAL_ctxSentence_TRAIN_all_TEST_NULL_second_train_set_null_False
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- This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0658
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- - Precision: 0.9900
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- - Recall: 0.9908
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  - F1: 0.9904
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  - Accuracy: 0.9814
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 479 | 0.3565 | 0.8698 | 0.9243 | 0.8962 | 0.8371 |
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- | 0.4677 | 2.0 | 958 | 0.3354 | 0.8894 | 0.9347 | 0.9115 | 0.8620 |
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- | 0.296 | 3.0 | 1437 | 0.3268 | 0.8931 | 0.9269 | 0.9097 | 0.8600 |
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- | 0.2264 | 4.0 | 1916 | 0.3519 | 0.8961 | 0.9347 | 0.9150 | 0.8679 |
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- | 0.1729 | 5.0 | 2395 | 0.3626 | 0.8960 | 0.9334 | 0.9143 | 0.8669 |
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  ### Framework versions
 
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  ---
 
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # DistilBERTFINAL_ctxSentence_TRAIN_all_TEST_NULL_second_train_set_null_False
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+ This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0557
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+ - Precision: 0.9930
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+ - Recall: 0.9878
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  - F1: 0.9904
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  - Accuracy: 0.9814
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 479 | 0.3334 | 0.9041 | 0.9041 | 0.9041 | 0.8550 |
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+ | 0.3756 | 2.0 | 958 | 0.3095 | 0.8991 | 0.9251 | 0.9119 | 0.8649 |
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+ | 0.2653 | 3.0 | 1437 | 0.3603 | 0.8929 | 0.9527 | 0.9218 | 0.8779 |
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+ | 0.1991 | 4.0 | 1916 | 0.3907 | 0.8919 | 0.9540 | 0.9219 | 0.8779 |
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+ | 0.1586 | 5.0 | 2395 | 0.3642 | 0.9070 | 0.9356 | 0.9211 | 0.8788 |
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  ### Framework versions