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bert-base-uncased-issues-128
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0420
- Micro f1: 0.6972
- Macro f1: 0.5740
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: 4
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Micro f1 | Macro f1 |
|---|---|---|---|---|---|
| 0.1542 | 1.0 | 404 | 0.0850 | 0.0 | 0.0 |
| 0.0853 | 2.0 | 808 | 0.0826 | 0.0 | 0.0 |
| 0.0828 | 3.0 | 1212 | 0.0776 | 0.0 | 0.0 |
| 0.0734 | 4.0 | 1616 | 0.0673 | 0.1735 | 0.0294 |
| 0.061 | 5.0 | 2020 | 0.0597 | 0.3500 | 0.0797 |
| 0.049 | 6.0 | 2424 | 0.0556 | 0.4449 | 0.1180 |
| 0.0398 | 7.0 | 2828 | 0.0497 | 0.5027 | 0.1615 |
| 0.0321 | 8.0 | 3232 | 0.0472 | 0.5609 | 0.2498 |
| 0.0261 | 9.0 | 3636 | 0.0481 | 0.5212 | 0.2442 |
| 0.0218 | 10.0 | 4040 | 0.0441 | 0.6238 | 0.3251 |
| 0.0182 | 11.0 | 4444 | 0.0423 | 0.6346 | 0.3880 |
| 0.0154 | 12.0 | 4848 | 0.0412 | 0.6573 | 0.4223 |
| 0.0126 | 13.0 | 5252 | 0.0419 | 0.6586 | 0.4570 |
| 0.0109 | 14.0 | 5656 | 0.0416 | 0.6646 | 0.4813 |
| 0.0092 | 15.0 | 6060 | 0.0401 | 0.6677 | 0.5041 |
| 0.0079 | 16.0 | 6464 | 0.0412 | 0.6859 | 0.5323 |
| 0.0068 | 17.0 | 6868 | 0.0435 | 0.6667 | 0.5372 |
| 0.0059 | 18.0 | 7272 | 0.0452 | 0.6735 | 0.5617 |
| 0.0053 | 19.0 | 7676 | 0.0420 | 0.6735 | 0.5590 |
| 0.0042 | 20.0 | 8080 | 0.0420 | 0.6972 | 0.5740 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.11.0
