test-model_ROBERTA
This model is a fine-tuned version of roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2733
- Rmse: 0.3427
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 16
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Rmse |
| 0.6755 |
2.72 |
500 |
0.4136 |
0.5126 |
| 0.1909 |
5.43 |
1000 |
0.2733 |
0.3427 |
| 0.0784 |
8.15 |
1500 |
0.3173 |
0.3244 |
| 0.0382 |
10.86 |
2000 |
0.3523 |
0.3039 |
| 0.0213 |
13.58 |
2500 |
0.3947 |
0.2866 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3
