metadata
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: STS-conventional-Fine-Tuning-Capstone-roberta-base-filtered-170
results: []
STS-conventional-Fine-Tuning-Capstone-roberta-base-filtered-170
This model is a fine-tuned version of FacebookAI/roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.3403
- Accuracy: 0.7285
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 113 | 0.7529 | 0.6816 |
| No log | 2.0 | 226 | 0.7985 | 0.7097 |
| No log | 3.0 | 339 | 0.8245 | 0.7097 |
| No log | 4.0 | 452 | 0.8816 | 0.6798 |
| 0.5011 | 5.0 | 565 | 1.0854 | 0.6929 |
| 0.5011 | 6.0 | 678 | 1.1921 | 0.7135 |
| 0.5011 | 7.0 | 791 | 1.3839 | 0.7228 |
| 0.5011 | 8.0 | 904 | 1.4560 | 0.7247 |
| 0.1649 | 9.0 | 1017 | 1.6387 | 0.7191 |
| 0.1649 | 10.0 | 1130 | 1.8012 | 0.7172 |
| 0.1649 | 11.0 | 1243 | 1.8790 | 0.7247 |
| 0.1649 | 12.0 | 1356 | 2.0223 | 0.7116 |
| 0.1649 | 13.0 | 1469 | 2.0297 | 0.7228 |
| 0.0639 | 14.0 | 1582 | 2.1202 | 0.7228 |
| 0.0639 | 15.0 | 1695 | 2.2489 | 0.7303 |
| 0.0639 | 16.0 | 1808 | 2.2505 | 0.7266 |
| 0.0639 | 17.0 | 1921 | 2.2693 | 0.7303 |
| 0.0198 | 18.0 | 2034 | 2.3216 | 0.7228 |
| 0.0198 | 19.0 | 2147 | 2.3244 | 0.7247 |
| 0.0198 | 20.0 | 2260 | 2.3403 | 0.7285 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2