| | --- |
| | license: apache-2.0 |
| | base_model: bert-base-uncased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - precision |
| | - recall |
| | model-index: |
| | - name: AugWordNet_BERT_FPB_finetuned |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # AugWordNet_BERT_FPB_finetuned |
| | |
| | This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.3789 |
| | - Accuracy: 0.9097 |
| | - F1: 0.9100 |
| | - Precision: 0.9140 |
| | - Recall: 0.9097 |
| | |
| | ## 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: 0.0001 |
| | - train_batch_size: 64 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 1000 |
| | - num_epochs: 10 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | | 0.8426 | 1.0 | 91 | 0.7693 | 0.6978 | 0.6777 | 0.6887 | 0.6978 | |
| | | 0.4269 | 2.0 | 182 | 0.3264 | 0.8816 | 0.8803 | 0.8820 | 0.8816 | |
| | | 0.3055 | 3.0 | 273 | 0.2990 | 0.8832 | 0.8838 | 0.8888 | 0.8832 | |
| | | 0.2135 | 4.0 | 364 | 0.3049 | 0.9003 | 0.8998 | 0.9006 | 0.9003 | |
| | | 0.1275 | 5.0 | 455 | 0.3764 | 0.8801 | 0.8786 | 0.8839 | 0.8801 | |
| | | 0.1033 | 6.0 | 546 | 0.3393 | 0.9019 | 0.9007 | 0.9048 | 0.9019 | |
| | | 0.0635 | 7.0 | 637 | 0.3829 | 0.9081 | 0.9079 | 0.9082 | 0.9081 | |
| | | 0.0657 | 8.0 | 728 | 0.4759 | 0.8972 | 0.8958 | 0.8986 | 0.8972 | |
| | | 0.0548 | 9.0 | 819 | 0.3789 | 0.9097 | 0.9100 | 0.9140 | 0.9097 | |
| | | 0.0695 | 10.0 | 910 | 0.4797 | 0.8894 | 0.8876 | 0.8979 | 0.8894 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.37.0 |
| | - Pytorch 2.1.2 |
| | - Datasets 2.1.0 |
| | - Tokenizers 0.15.1 |
| |
|
