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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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datasets: |
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- token_classification_v2 |
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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: favs_token_classification_v2_uncased |
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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: token_classification_v2 |
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type: token_classification_v2 |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.6598639455782312 |
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- name: Recall |
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type: recall |
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value: 0.782258064516129 |
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- name: F1 |
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type: f1 |
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value: 0.7158671586715867 |
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- name: Accuracy |
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type: accuracy |
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value: 0.8546511627906976 |
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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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# favs_token_classification_v2_uncased |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the token_classification_v2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5006 |
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- Precision: 0.6599 |
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- Recall: 0.7823 |
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- F1: 0.7159 |
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- Accuracy: 0.8547 |
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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: 1.5e-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: 20 |
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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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| 2.2447 | 1.0 | 13 | 1.9089 | 0.2 | 0.0968 | 0.1304 | 0.3576 | |
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| 1.9589 | 2.0 | 26 | 1.5848 | 0.2734 | 0.2823 | 0.2778 | 0.4477 | |
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| 1.729 | 3.0 | 39 | 1.3636 | 0.3128 | 0.4516 | 0.3696 | 0.6134 | |
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| 1.4278 | 4.0 | 52 | 1.1854 | 0.4302 | 0.5968 | 0.5 | 0.7122 | |
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| 1.3046 | 5.0 | 65 | 1.0341 | 0.5183 | 0.6855 | 0.5903 | 0.7413 | |
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| 1.1599 | 6.0 | 78 | 0.9163 | 0.5188 | 0.6694 | 0.5845 | 0.75 | |
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| 0.9263 | 7.0 | 91 | 0.8235 | 0.5399 | 0.7097 | 0.6132 | 0.7645 | |
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| 0.8721 | 8.0 | 104 | 0.7627 | 0.5176 | 0.7097 | 0.5986 | 0.7733 | |
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| 0.7879 | 9.0 | 117 | 0.7070 | 0.5366 | 0.7097 | 0.6111 | 0.7849 | |
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| 0.6881 | 10.0 | 130 | 0.6575 | 0.5427 | 0.7177 | 0.6181 | 0.7936 | |
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| 0.6414 | 11.0 | 143 | 0.6076 | 0.5660 | 0.7258 | 0.6360 | 0.8110 | |
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| 0.6096 | 12.0 | 156 | 0.5804 | 0.6090 | 0.7661 | 0.6786 | 0.8285 | |
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| 0.5812 | 13.0 | 169 | 0.5661 | 0.6282 | 0.7903 | 0.7000 | 0.8343 | |
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| 0.5006 | 14.0 | 182 | 0.5503 | 0.6144 | 0.7581 | 0.6787 | 0.8285 | |
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| 0.5289 | 15.0 | 195 | 0.5366 | 0.6267 | 0.7581 | 0.6861 | 0.8372 | |
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| 0.4447 | 16.0 | 208 | 0.5222 | 0.6419 | 0.7661 | 0.6985 | 0.8459 | |
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| 0.435 | 17.0 | 221 | 0.5120 | 0.6599 | 0.7823 | 0.7159 | 0.8517 | |
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| 0.4454 | 18.0 | 234 | 0.5058 | 0.6667 | 0.7903 | 0.7232 | 0.8547 | |
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| 0.422 | 19.0 | 247 | 0.5013 | 0.6599 | 0.7823 | 0.7159 | 0.8547 | |
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| 0.4285 | 20.0 | 260 | 0.5006 | 0.6599 | 0.7823 | 0.7159 | 0.8547 | |
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### Framework versions |
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- Transformers 4.21.1 |
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- Pytorch 1.12.1 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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