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SharonTudi
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DIALOGUE_second_model

Text Classification
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bert
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End of training

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  1. README.md +11 -11
  2. model.safetensors +1 -1
  3. runs/Jan21_11-46-54_1a3a957c2842/events.out.tfevents.1705837617.1a3a957c2842.8067.6 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -20,7 +20,7 @@ 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 the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1712
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  - Precision: 0.9762
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  - Recall: 0.9737
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  - F1: 0.9736
@@ -43,7 +43,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 6e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -55,15 +55,15 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 1.1142 | 0.31 | 15 | 0.5951 | 0.8845 | 0.8289 | 0.8156 | 0.8289 |
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- | 0.4102 | 0.62 | 30 | 0.2140 | 0.9327 | 0.9211 | 0.9204 | 0.9211 |
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- | 0.2904 | 0.94 | 45 | 0.1306 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0982 | 1.25 | 60 | 0.1004 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0932 | 1.56 | 75 | 0.1107 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0787 | 1.88 | 90 | 0.2268 | 0.9421 | 0.9342 | 0.9313 | 0.9342 |
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- | 0.0088 | 2.19 | 105 | 0.1687 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0294 | 2.5 | 120 | 0.1946 | 0.9637 | 0.9605 | 0.9604 | 0.9605 |
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- | 0.0091 | 2.81 | 135 | 0.1712 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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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 the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3499
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  - Precision: 0.9762
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  - Recall: 0.9737
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  - F1: 0.9736
 
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 1.3735 | 0.31 | 15 | 1.3341 | 0.2562 | 0.4868 | 0.3323 | 0.4868 |
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+ | 1.2891 | 0.62 | 30 | 1.1793 | 0.8546 | 0.7368 | 0.6683 | 0.7368 |
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+ | 1.1 | 0.94 | 45 | 0.9372 | 0.9421 | 0.9342 | 0.9339 | 0.9342 |
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+ | 0.884 | 1.25 | 60 | 0.7268 | 0.9524 | 0.9474 | 0.9472 | 0.9474 |
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+ | 0.7087 | 1.56 | 75 | 0.5780 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.6158 | 1.88 | 90 | 0.4773 | 0.9327 | 0.9211 | 0.9204 | 0.9211 |
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+ | 0.5052 | 2.19 | 105 | 0.4043 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.4321 | 2.5 | 120 | 0.3652 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.4412 | 2.81 | 135 | 0.3499 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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  ### Framework versions
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