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--- |
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license: apache-2.0 |
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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: distilbert-base-uncased-finetuned-ner-TRANS |
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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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# distilbert-base-uncased-finetuned-ner-TRANS |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1053 |
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- Precision: 0.7911 |
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- Recall: 0.8114 |
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- F1: 0.8011 |
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- Accuracy: 0.9815 |
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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: 2e-05 |
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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: 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: 12 |
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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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| 0.077 | 1.0 | 3762 | 0.0724 | 0.7096 | 0.7472 | 0.7279 | 0.9741 | |
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| 0.0538 | 2.0 | 7524 | 0.0652 | 0.7308 | 0.7687 | 0.7493 | 0.9766 | |
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| 0.0412 | 3.0 | 11286 | 0.0643 | 0.7672 | 0.7875 | 0.7772 | 0.9788 | |
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| 0.0315 | 4.0 | 15048 | 0.0735 | 0.7646 | 0.7966 | 0.7803 | 0.9793 | |
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| 0.0249 | 5.0 | 18810 | 0.0772 | 0.7805 | 0.7981 | 0.7892 | 0.9801 | |
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| 0.0213 | 6.0 | 22572 | 0.0783 | 0.7829 | 0.8063 | 0.7944 | 0.9805 | |
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| 0.0187 | 7.0 | 26334 | 0.0858 | 0.7821 | 0.8010 | 0.7914 | 0.9809 | |
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| 0.0157 | 8.0 | 30096 | 0.0860 | 0.7837 | 0.8120 | 0.7976 | 0.9812 | |
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| 0.0122 | 9.0 | 33858 | 0.0963 | 0.7857 | 0.8129 | 0.7990 | 0.9813 | |
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| 0.0107 | 10.0 | 37620 | 0.0993 | 0.7934 | 0.8089 | 0.8010 | 0.9812 | |
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| 0.0091 | 11.0 | 41382 | 0.1031 | 0.7882 | 0.8123 | 0.8001 | 0.9814 | |
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| 0.0083 | 12.0 | 45144 | 0.1053 | 0.7911 | 0.8114 | 0.8011 | 0.9815 | |
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### Framework versions |
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- Transformers 4.15.0 |
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- Pytorch 1.10.1 |
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- Datasets 2.0.0 |
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- Tokenizers 0.10.3 |
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