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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- skript |
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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-finetuned-ner |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: skript |
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type: skript |
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args: conll2003 |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.058091286307053944 |
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- name: Recall |
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type: recall |
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value: 0.04498714652956298 |
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- name: F1 |
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type: f1 |
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value: 0.05070626584570808 |
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- name: Accuracy |
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type: accuracy |
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value: 0.7974446689319497 |
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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-finetuned-ner |
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This model was trained from scratch on the skript dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6713 |
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- Precision: 0.0581 |
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- Recall: 0.0450 |
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- F1: 0.0507 |
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- Accuracy: 0.7974 |
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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: 3 |
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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 | 44 | 0.8207 | 0.0 | 0.0 | 0.0 | 0.7748 | |
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| No log | 2.0 | 88 | 0.7113 | 0.0405 | 0.0231 | 0.0294 | 0.7889 | |
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| No log | 3.0 | 132 | 0.6713 | 0.0581 | 0.0450 | 0.0507 | 0.7974 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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