Training complete
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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model:
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tags:
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- generated_from_trainer
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metrics:
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# bert-finetuned-ner
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This model is a fine-tuned version of [
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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.
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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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---
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library_name: transformers
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license: apache-2.0
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base_model: albert/albert-base-v1
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tags:
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- generated_from_trainer
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metrics:
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# bert-finetuned-ner
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This model is a fine-tuned version of [albert/albert-base-v1](https://huggingface.co/albert/albert-base-v1) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0994
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- Precision: 0.9628
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- Recall: 0.9740
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- F1: 0.9683
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- Accuracy: 0.9813
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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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| 0.0688 | 1.0 | 5285 | 0.1227 | 0.9555 | 0.9670 | 0.9612 | 0.9769 |
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| 0.0583 | 2.0 | 10570 | 0.1051 | 0.9581 | 0.9723 | 0.9652 | 0.9803 |
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| 0.0798 | 3.0 | 15855 | 0.0994 | 0.9628 | 0.9740 | 0.9683 | 0.9813 |
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### Framework versions
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