End of training
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README.md
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metrics:
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- name: Precision
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type: precision
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value: 0.
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- name: Recall
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type: recall
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value: 0.
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- name: F1
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type: f1
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- name: Accuracy
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type: accuracy
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the conll2003 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.9322
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- Accuracy: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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### Framework versions
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metrics:
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- name: Precision
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type: precision
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value: 0.9273773939997786
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- name: Recall
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type: recall
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value: 0.9371294328224634
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- name: F1
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type: f1
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value: 0.9322279100823503
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- name: Accuracy
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type: accuracy
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value: 0.9834146186474335
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the conll2003 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0618
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- Precision: 0.9274
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- Recall: 0.9371
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- F1: 0.9322
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- Accuracy: 0.9834
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.253 | 1.0 | 878 | 0.0708 | 0.9027 | 0.9177 | 0.9101 | 0.9795 |
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| 0.0518 | 2.0 | 1756 | 0.0624 | 0.9204 | 0.9329 | 0.9266 | 0.9825 |
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| 0.031 | 3.0 | 2634 | 0.0618 | 0.9274 | 0.9371 | 0.9322 | 0.9834 |
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### Framework versions
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model.safetensors
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