| --- |
| license: mit |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: roberta-base_fold_1_binary_v1 |
| 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. --> |
|
|
| # roberta-base_fold_1_binary_v1 |
|
|
| This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.4984 |
| - F1: 0.8339 |
|
|
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 25 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | No log | 1.0 | 288 | 0.3819 | 0.8117 | |
| | 0.4108 | 2.0 | 576 | 0.3696 | 0.8281 | |
| | 0.4108 | 3.0 | 864 | 0.4890 | 0.8343 | |
| | 0.2261 | 4.0 | 1152 | 0.7605 | 0.8298 | |
| | 0.2261 | 5.0 | 1440 | 0.7754 | 0.8307 | |
| | 0.1404 | 6.0 | 1728 | 0.7650 | 0.8174 | |
| | 0.0962 | 7.0 | 2016 | 0.8539 | 0.8315 | |
| | 0.0962 | 8.0 | 2304 | 1.0770 | 0.8263 | |
| | 0.0433 | 9.0 | 2592 | 1.1450 | 0.8292 | |
| | 0.0433 | 10.0 | 2880 | 1.1700 | 0.8205 | |
| | 0.0344 | 11.0 | 3168 | 1.2376 | 0.8241 | |
| | 0.0344 | 12.0 | 3456 | 1.2688 | 0.8329 | |
| | 0.0219 | 13.0 | 3744 | 1.3276 | 0.8283 | |
| | 0.0123 | 14.0 | 4032 | 1.2930 | 0.8320 | |
| | 0.0123 | 15.0 | 4320 | 1.4631 | 0.8266 | |
| | 0.0177 | 16.0 | 4608 | 1.4326 | 0.8270 | |
| | 0.0177 | 17.0 | 4896 | 1.4770 | 0.8334 | |
| | 0.0053 | 18.0 | 5184 | 1.5972 | 0.8214 | |
| | 0.0053 | 19.0 | 5472 | 1.5331 | 0.8327 | |
| | 0.0045 | 20.0 | 5760 | 1.5487 | 0.8359 | |
| | 0.0086 | 21.0 | 6048 | 1.4610 | 0.8315 | |
| | 0.0086 | 22.0 | 6336 | 1.4685 | 0.8353 | |
| | 0.0071 | 23.0 | 6624 | 1.4933 | 0.8358 | |
| | 0.0071 | 24.0 | 6912 | 1.4898 | 0.8310 | |
| | 0.0022 | 25.0 | 7200 | 1.4984 | 0.8339 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.21.1 |
| - Pytorch 1.12.0+cu113 |
| - Datasets 2.4.0 |
| - Tokenizers 0.12.1 |
|
|
