| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - finer-139 | |
| - nlpaueb/finer-139 | |
| metrics: | |
| - precision | |
| - recall | |
| - f1 | |
| - accuracy | |
| base_model: google/bert_uncased_L-2_H-128_A-2 | |
| model-index: | |
| - name: bertiny-finetuned-finer | |
| results: | |
| - task: | |
| type: token-classification | |
| name: Token Classification | |
| dataset: | |
| name: finer-139 | |
| type: finer-139 | |
| args: finer-139 | |
| metrics: | |
| - type: precision | |
| value: 0.5339285714285714 | |
| name: Precision | |
| - type: recall | |
| value: 0.036011080332409975 | |
| name: Recall | |
| - type: f1 | |
| value: 0.06747151077513258 | |
| name: F1 | |
| - type: accuracy | |
| value: 0.9847166143263048 | |
| name: Accuracy | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # bertiny-finetuned-finer | |
| This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the finer-139 dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0882 | |
| - Precision: 0.5339 | |
| - Recall: 0.0360 | |
| - F1: 0.0675 | |
| - Accuracy: 0.9847 | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| More information needed | |
| ## Training procedure | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| - learning_rate: 2e-05 | |
| - train_batch_size: 8 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | | |
| |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| | |
| | 0.0871 | 1.0 | 11255 | 0.0952 | 0.0 | 0.0 | 0.0 | 0.9843 | | |
| | 0.0864 | 2.0 | 22510 | 0.0895 | 0.7640 | 0.0082 | 0.0162 | 0.9844 | | |
| | 0.0929 | 3.0 | 33765 | 0.0882 | 0.5339 | 0.0360 | 0.0675 | 0.9847 | | |
| ### Framework versions | |
| - Transformers 4.20.1 | |
| - Pytorch 1.12.0+cu113 | |
| - Datasets 2.3.2 | |
| - Tokenizers 0.12.1 | |