Training complete
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README.md
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model-index:
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- name: bert-finetuned-ner
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results: []
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datasets:
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- conll2002
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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 [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown 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.
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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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- Transformers 4.40.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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model-index:
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- name: bert-finetuned-ner
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results: []
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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 [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1471
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- Precision: 0.7369
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- Recall: 0.7943
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- F1: 0.7646
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- Accuracy: 0.9666
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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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| 0.1691 | 1.0 | 521 | 0.1438 | 0.6830 | 0.7371 | 0.7090 | 0.9587 |
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| 0.076 | 2.0 | 1042 | 0.1402 | 0.7075 | 0.7670 | 0.7361 | 0.9622 |
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| 0.05 | 3.0 | 1563 | 0.1332 | 0.7536 | 0.7971 | 0.7748 | 0.9672 |
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| 0.0359 | 4.0 | 2084 | 0.1442 | 0.7420 | 0.7845 | 0.7626 | 0.9663 |
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| 0.0265 | 5.0 | 2605 | 0.1471 | 0.7369 | 0.7943 | 0.7646 | 0.9666 |
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### Framework versions
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- Transformers 4.40.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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