|
--- |
|
license: mit |
|
base_model: ryantaw/bert-small-finetuned |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: bert-small-finetuned-finetuned |
|
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. --> |
|
|
|
# bert-small-finetuned-finetuned |
|
|
|
This model is a fine-tuned version of [ryantaw/bert-small-finetuned](https://huggingface.co/ryantaw/bert-small-finetuned) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.8577 |
|
- Accuracy: 0.6846 |
|
- F1 Score: 0.6854 |
|
|
|
## 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: 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 | 0.8402 | 0.6577 | 0.6553 | |
|
| No log | 2.0 | 372 | 0.8577 | 0.6846 | 0.6854 | |
|
| 0.7061 | 3.0 | 558 | 0.9049 | 0.6415 | 0.6367 | |
|
| 0.7061 | 4.0 | 744 | 0.9252 | 0.6631 | 0.6625 | |
|
| 0.7061 | 5.0 | 930 | 1.0010 | 0.6685 | 0.6670 | |
|
| 0.3613 | 6.0 | 1116 | 1.1754 | 0.6199 | 0.6130 | |
|
| 0.3613 | 7.0 | 1302 | 1.2138 | 0.6604 | 0.6592 | |
|
| 0.3613 | 8.0 | 1488 | 1.3055 | 0.6604 | 0.6583 | |
|
| 0.1426 | 9.0 | 1674 | 1.3710 | 0.6523 | 0.6495 | |
|
| 0.1426 | 10.0 | 1860 | 1.3899 | 0.6550 | 0.6529 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.0 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|
