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SimoneJLaudani
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trainer2

Text Classification
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distilbert
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End of training

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  1. README.md +16 -16
  2. model.safetensors +1 -1
  3. runs/Mar19_20-33-39_f2dbfe237d11/events.out.tfevents.1710880433.f2dbfe237d11.373.8 +3 -0
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  5. runs/Mar19_20-42-48_f2dbfe237d11/events.out.tfevents.1710880973.f2dbfe237d11.373.10 +3 -0
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  10. tokenizer.json +0 -0
  11. tokenizer_config.json +0 -2
  12. training_args.bin +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ 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 the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0083
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- - Precision: 1.0
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- - Recall: 1.0
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- - F1: 1.0
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- - Accuracy: 1.0
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  ## Model description
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@@ -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: 2e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -53,16 +53,16 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
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- | 0.2385 | 0.57 | 30 | 0.0803 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0738 | 1.13 | 60 | 0.0324 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0382 | 1.7 | 90 | 0.0195 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0263 | 2.26 | 120 | 0.0142 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0204 | 2.83 | 150 | 0.0115 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0172 | 3.4 | 180 | 0.0099 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0148 | 3.96 | 210 | 0.0090 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.014 | 4.53 | 240 | 0.0085 | 1.0 | 1.0 | 1.0 | 1.0 |
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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: 2.5691
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+ - Precision: 0.6582
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+ - Recall: 0.6071
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+ - F1: 0.6064
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+ - Accuracy: 0.6071
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  ## Model description
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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
 
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.1561 | 0.57 | 30 | 3.7469 | 0.4468 | 0.3690 | 0.3388 | 0.3690 |
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+ | 0.0728 | 1.13 | 60 | 2.5416 | 0.6275 | 0.5952 | 0.5839 | 0.5952 |
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+ | 0.0016 | 1.7 | 90 | 2.4746 | 0.6998 | 0.6548 | 0.6492 | 0.6548 |
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+ | 0.0194 | 2.26 | 120 | 2.8199 | 0.6492 | 0.5952 | 0.6011 | 0.5952 |
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+ | 0.0032 | 2.83 | 150 | 2.7695 | 0.6307 | 0.5595 | 0.5562 | 0.5595 |
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+ | 0.0028 | 3.4 | 180 | 2.8934 | 0.6442 | 0.5952 | 0.5928 | 0.5952 |
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+ | 0.003 | 3.96 | 210 | 2.6995 | 0.6613 | 0.6071 | 0.6024 | 0.6071 |
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+ | 0.0003 | 4.53 | 240 | 2.5716 | 0.6582 | 0.6071 | 0.6064 | 0.6071 |
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  ### Framework versions
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