|
--- |
|
license: mit |
|
base_model: roberta-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- f1 |
|
model-index: |
|
- name: roberta-base-Roberta-Model |
|
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. --> |
|
|
|
# roberta-base-Roberta-Model |
|
|
|
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7350 |
|
- F1: 0.6663 |
|
|
|
## 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: 5e-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 | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 0.8512 | 0.5 | 500 | 0.7909 | 0.6405 | |
|
| 0.7992 | 1.0 | 1000 | 0.8753 | 0.6407 | |
|
| 0.7667 | 1.5 | 1500 | 0.7786 | 0.6428 | |
|
| 0.7583 | 2.01 | 2000 | 0.7407 | 0.6593 | |
|
| 0.7415 | 2.51 | 2500 | 0.7564 | 0.6555 | |
|
| 0.7337 | 3.01 | 3000 | 0.7536 | 0.6526 | |
|
| 0.7224 | 3.51 | 3500 | 0.7777 | 0.6126 | |
|
| 0.7067 | 4.01 | 4000 | 0.7790 | 0.6552 | |
|
| 0.6693 | 4.51 | 4500 | 0.7497 | 0.6665 | |
|
| 0.6744 | 5.02 | 5000 | 0.7350 | 0.6663 | |
|
| 0.6546 | 5.52 | 5500 | 0.7865 | 0.6714 | |
|
| 0.6725 | 6.02 | 6000 | 0.7639 | 0.6721 | |
|
| 0.6361 | 6.52 | 6500 | 0.7780 | 0.6917 | |
|
| 0.6268 | 7.02 | 7000 | 0.7905 | 0.6893 | |
|
| 0.619 | 7.52 | 7500 | 0.7644 | 0.6991 | |
|
| 0.6008 | 8.02 | 8000 | 0.7473 | 0.7086 | |
|
| 0.5824 | 8.53 | 8500 | 0.7601 | 0.7009 | |
|
| 0.5687 | 9.03 | 9000 | 0.7795 | 0.6888 | |
|
| 0.5466 | 9.53 | 9500 | 0.7925 | 0.7045 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.33.0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.14.4 |
|
- Tokenizers 0.13.3 |
|
|
