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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: test-ner |
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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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# test-ner |
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This model was trained from scratch on an unkown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4357 |
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- Precision: 0.0 |
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- Recall: 0.0 |
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- F1: 0.0 |
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- Accuracy: 0.8863 |
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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: 0.02 |
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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: 1 |
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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 | 340 | 0.4357 | 0.0 | 0.0 | 0.0 | 0.8863 | |
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### Framework versions |
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- Transformers 4.6.1 |
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- Pytorch 1.9.0 |
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- Datasets 1.6.2 |
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- Tokenizers 0.10.3 |
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