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distilbert_finetune_own_data_model

Token Classification
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distilbert
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End of training

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  1. README.md +14 -14
  2. model.safetensors +1 -1
  3. runs/Mar02_12-01-47_062f85bf131e/events.out.tfevents.1709380922.062f85bf131e.268.19 +3 -0
  4. runs/Mar02_12-01-47_062f85bf131e/events.out.tfevents.1709380993.062f85bf131e.268.20 +3 -0
  5. 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-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0185
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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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  ### 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
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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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- | No log | 1.0 | 5 | 0.4954 | 0.0 | 0.0 | 0.0 | 0.72 |
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- | No log | 2.0 | 10 | 0.3449 | 0.75 | 0.6 | 0.6667 | 0.92 |
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- | No log | 3.0 | 15 | 0.2080 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 4.0 | 20 | 0.1169 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 5.0 | 25 | 0.0606 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 6.0 | 30 | 0.0353 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 7.0 | 35 | 0.0258 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 8.0 | 40 | 0.0212 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 9.0 | 45 | 0.0191 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 10.0 | 50 | 0.0185 | 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-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0004
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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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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5e-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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+ | No log | 1.0 | 5 | 0.2706 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 2.0 | 10 | 0.0471 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 3.0 | 15 | 0.0058 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 4.0 | 20 | 0.0018 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 5.0 | 25 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 6.0 | 30 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 7.0 | 35 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 8.0 | 40 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 9.0 | 45 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 10.0 | 50 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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  ### Framework versions
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