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: 0.9943
- Accuracy: 0.5822
- F1 Score: 0.5820
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: 1.0136026165598675e-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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
|---|---|---|---|---|---|
| No log | 1.0 | 186 | 1.1631 | 0.4636 | 0.4346 |
| No log | 2.0 | 372 | 1.0563 | 0.5553 | 0.5558 |
| 1.1271 | 3.0 | 558 | 1.0238 | 0.5633 | 0.5629 |
| 1.1271 | 4.0 | 744 | 0.9990 | 0.5795 | 0.5786 |
| 1.1271 | 5.0 | 930 | 0.9943 | 0.5822 | 0.5820 |
| 0.8392 | 6.0 | 1116 | 1.0389 | 0.5741 | 0.5692 |
| 0.8392 | 7.0 | 1302 | 1.0114 | 0.5768 | 0.5759 |
| 0.8392 | 8.0 | 1488 | 1.0277 | 0.5741 | 0.5702 |
| 0.692 | 9.0 | 1674 | 1.0246 | 0.5822 | 0.5799 |
| 0.692 | 10.0 | 1860 | 1.0241 | 0.5822 | 0.5797 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1