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ae-314
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token_classification_wnut_model

Token Classification
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distilbert
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End of training

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  1. README.md +12 -9
  2. model.safetensors +1 -1
  3. runs/Oct18_06-41-08_b1d7bac1bef8/events.out.tfevents.1760769669.b1d7bac1bef8.678.15 +2 -2
README.md CHANGED
@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [ae-314/token_classification_wnut_model](https://huggingface.co/ae-314/token_classification_wnut_model) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3163
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- - Precision: 0.5284
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- - Recall: 0.3883
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- - F1: 0.4476
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- - Accuracy: 0.9466
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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: 2e-07
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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- - num_epochs: 2
 
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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 | 213 | 0.3164 | 0.5332 | 0.3874 | 0.4487 | 0.9467 |
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- | No log | 2.0 | 426 | 0.3163 | 0.5284 | 0.3883 | 0.4476 | 0.9466 |
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [ae-314/token_classification_wnut_model](https://huggingface.co/ae-314/token_classification_wnut_model) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3924
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+ - Precision: 0.5017
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+ - Recall: 0.4124
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+ - F1: 0.4527
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+ - Accuracy: 0.9446
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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: 1e-09
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 4
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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 | 213 | 0.3924 | 0.5017 | 0.4124 | 0.4527 | 0.9446 |
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+ | No log | 2.0 | 426 | 0.3924 | 0.5017 | 0.4124 | 0.4527 | 0.9446 |
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+ | 0.0022 | 3.0 | 639 | 0.3924 | 0.5017 | 0.4124 | 0.4527 | 0.9446 |
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+ | 0.0022 | 4.0 | 852 | 0.3924 | 0.5017 | 0.4124 | 0.4527 | 0.9446 |
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  ### Framework versions
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