metadata
license: mit
base_model: prajjwal1/bert-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-small-finetuned
results: []
bert-small-finetuned
This model is a fine-tuned version of prajjwal1/bert-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9941
- Accuracy: 0.5903
- F1 Score: 0.5865
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
|---|---|---|---|---|---|
| No log | 1.0 | 24 | 1.2145 | 0.4933 | 0.4701 |
| No log | 2.0 | 48 | 1.0960 | 0.5391 | 0.5365 |
| No log | 3.0 | 72 | 1.0569 | 0.5768 | 0.5791 |
| No log | 4.0 | 96 | 1.0052 | 0.5714 | 0.5698 |
| No log | 5.0 | 120 | 0.9889 | 0.5714 | 0.5702 |
| No log | 6.0 | 144 | 0.9932 | 0.5795 | 0.5772 |
| No log | 7.0 | 168 | 0.9841 | 0.5714 | 0.5680 |
| No log | 8.0 | 192 | 0.9941 | 0.5903 | 0.5865 |
| No log | 9.0 | 216 | 0.9788 | 0.5903 | 0.5891 |
| No log | 10.0 | 240 | 1.0105 | 0.5660 | 0.5617 |
| No log | 11.0 | 264 | 1.0473 | 0.5526 | 0.5464 |
| No log | 12.0 | 288 | 1.0272 | 0.5714 | 0.5685 |
| No log | 13.0 | 312 | 1.0627 | 0.5499 | 0.5492 |
| No log | 14.0 | 336 | 1.0428 | 0.5795 | 0.5782 |
| No log | 15.0 | 360 | 1.0644 | 0.5633 | 0.5625 |
| No log | 16.0 | 384 | 1.1463 | 0.5364 | 0.5261 |
| No log | 17.0 | 408 | 1.1109 | 0.5714 | 0.5689 |
| No log | 18.0 | 432 | 1.1260 | 0.5741 | 0.5739 |
| No log | 19.0 | 456 | 1.1793 | 0.5580 | 0.5533 |
| No log | 20.0 | 480 | 1.1968 | 0.5580 | 0.5535 |
| 0.6103 | 21.0 | 504 | 1.1961 | 0.5741 | 0.5722 |
| 0.6103 | 22.0 | 528 | 1.2399 | 0.5553 | 0.5504 |
| 0.6103 | 23.0 | 552 | 1.2642 | 0.5526 | 0.5473 |
| 0.6103 | 24.0 | 576 | 1.2530 | 0.5660 | 0.5625 |
| 0.6103 | 25.0 | 600 | 1.2637 | 0.5714 | 0.5687 |
| 0.6103 | 26.0 | 624 | 1.3012 | 0.5526 | 0.5468 |
| 0.6103 | 27.0 | 648 | 1.2932 | 0.5606 | 0.5579 |
| 0.6103 | 28.0 | 672 | 1.2888 | 0.5687 | 0.5664 |
| 0.6103 | 29.0 | 696 | 1.3087 | 0.5660 | 0.5634 |
| 0.6103 | 30.0 | 720 | 1.3073 | 0.5714 | 0.5687 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1