| --- |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: tiny_bb_wd |
| 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. --> |
|
|
| # tiny_bb_wd |
|
|
| This model is a fine-tuned version of [kktoto/tiny_bb_wd](https://huggingface.co/kktoto/tiny_bb_wd) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1331 |
| - Precision: 0.6566 |
| - Recall: 0.6502 |
| - F1: 0.6533 |
| - Accuracy: 0.9524 |
|
|
| ## 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: 3e-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: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.1193 | 1.0 | 5561 | 0.1398 | 0.6406 | 0.6264 | 0.6335 | 0.9501 | |
| | 0.1259 | 2.0 | 11122 | 0.1343 | 0.6476 | 0.6300 | 0.6387 | 0.9509 | |
| | 0.1283 | 3.0 | 16683 | 0.1333 | 0.6484 | 0.6367 | 0.6425 | 0.9512 | |
| | 0.1217 | 4.0 | 22244 | 0.1325 | 0.6524 | 0.6380 | 0.6451 | 0.9516 | |
| | 0.12 | 5.0 | 27805 | 0.1337 | 0.6571 | 0.6377 | 0.6472 | 0.9522 | |
| | 0.1187 | 6.0 | 33366 | 0.1319 | 0.6630 | 0.6297 | 0.6459 | 0.9525 | |
| | 0.116 | 7.0 | 38927 | 0.1318 | 0.6600 | 0.6421 | 0.6509 | 0.9525 | |
| | 0.1125 | 8.0 | 44488 | 0.1337 | 0.6563 | 0.6481 | 0.6522 | 0.9523 | |
| | 0.1118 | 9.0 | 50049 | 0.1329 | 0.6575 | 0.6477 | 0.6526 | 0.9524 | |
| | 0.1103 | 10.0 | 55610 | 0.1331 | 0.6566 | 0.6502 | 0.6533 | 0.9524 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.19.2 |
| - Pytorch 1.11.0+cu113 |
| - Datasets 2.2.2 |
| - Tokenizers 0.12.1 |
|
|
