<!-- 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. -->
albert-base-ours-run-1
This model is a fine-tuned version of albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.3970
- Accuracy: 0.735
- Precision: 0.7033
- Recall: 0.6790
- F1: 0.6873
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: 1e-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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.9719 | 1.0 | 200 | 0.8460 | 0.635 | 0.6534 | 0.5920 | 0.5547 |
| 0.7793 | 2.0 | 400 | 0.7762 | 0.675 | 0.6965 | 0.6323 | 0.5936 |
| 0.5734 | 3.0 | 600 | 0.8149 | 0.67 | 0.6200 | 0.6192 | 0.6196 |
| 0.3877 | 4.0 | 800 | 0.9555 | 0.7 | 0.6724 | 0.6482 | 0.6549 |
| 0.2426 | 5.0 | 1000 | 1.1248 | 0.695 | 0.6529 | 0.6437 | 0.6452 |
| 0.183 | 6.0 | 1200 | 1.3497 | 0.705 | 0.6717 | 0.6489 | 0.6563 |
| 0.1011 | 7.0 | 1400 | 1.6369 | 0.7 | 0.6620 | 0.6532 | 0.6560 |
| 0.0602 | 8.0 | 1600 | 1.8171 | 0.7 | 0.6763 | 0.6615 | 0.6654 |
| 0.0335 | 9.0 | 1800 | 1.9601 | 0.695 | 0.6640 | 0.6490 | 0.6545 |
| 0.0158 | 10.0 | 2000 | 2.0206 | 0.71 | 0.6802 | 0.6751 | 0.6768 |
| 0.0148 | 11.0 | 2200 | 2.0881 | 0.675 | 0.6252 | 0.6242 | 0.6232 |
| 0.0057 | 12.0 | 2400 | 2.2708 | 0.735 | 0.7146 | 0.6790 | 0.6904 |
| 0.0079 | 13.0 | 2600 | 2.2348 | 0.72 | 0.6917 | 0.6659 | 0.6746 |
| 0.0018 | 14.0 | 2800 | 2.2978 | 0.725 | 0.6968 | 0.6662 | 0.6761 |
| 0.0025 | 15.0 | 3000 | 2.3180 | 0.735 | 0.7067 | 0.6790 | 0.6883 |
| 0.0028 | 16.0 | 3200 | 2.3910 | 0.74 | 0.7153 | 0.6854 | 0.6953 |
| 0.0002 | 17.0 | 3400 | 2.3830 | 0.735 | 0.7033 | 0.6790 | 0.6873 |
| 0.0002 | 18.0 | 3600 | 2.3899 | 0.735 | 0.7033 | 0.6790 | 0.6873 |
| 0.0001 | 19.0 | 3800 | 2.3922 | 0.735 | 0.7033 | 0.6790 | 0.6873 |
| 0.0001 | 20.0 | 4000 | 2.3970 | 0.735 | 0.7033 | 0.6790 | 0.6873 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Tokenizers 0.13.2
