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--- |
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base_model: vitus9988/klue-roberta-small-ner-identified |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: klue-roberta-small-ner-identified |
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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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should probably proofread and complete it, then remove this comment. --> |
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# klue-roberta-small-ner-identified |
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This model is a fine-tuned version of [vitus9988/klue-roberta-small-ner-identified](https://huggingface.co/vitus9988/klue-roberta-small-ner-identified) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1304 |
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- Precision: 0.9222 |
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- Recall: 0.9520 |
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- F1: 0.9369 |
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- Accuracy: 0.9790 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 8 |
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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 | 4 | 0.8023 | 0.1377 | 0.1231 | 0.1300 | 0.9178 | |
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| No log | 2.0 | 8 | 0.4197 | 0.5419 | 0.5580 | 0.5498 | 0.9431 | |
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| No log | 3.0 | 12 | 0.2760 | 0.6764 | 0.7146 | 0.6950 | 0.9564 | |
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| No log | 4.0 | 16 | 0.2062 | 0.7835 | 0.8544 | 0.8174 | 0.9617 | |
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| No log | 5.0 | 20 | 0.1685 | 0.8299 | 0.8946 | 0.8610 | 0.9711 | |
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| No log | 6.0 | 24 | 0.1470 | 0.8854 | 0.9295 | 0.9069 | 0.9758 | |
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| No log | 7.0 | 28 | 0.1350 | 0.9138 | 0.9460 | 0.9297 | 0.9778 | |
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| No log | 8.0 | 32 | 0.1304 | 0.9222 | 0.9520 | 0.9369 | 0.9790 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0+cu118 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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