STS-conventional-Fine-Tuning-Capstone-roberta-base-filtered-270
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: 2.0848
- Accuracy: 0.7172
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: 15
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 113 | 0.7531 | 0.6854 |
No log | 2.0 | 226 | 0.7443 | 0.7060 |
No log | 3.0 | 339 | 0.9619 | 0.6779 |
No log | 4.0 | 452 | 0.8387 | 0.7022 |
0.4999 | 5.0 | 565 | 1.2001 | 0.6966 |
0.4999 | 6.0 | 678 | 1.2661 | 0.7060 |
0.4999 | 7.0 | 791 | 1.3723 | 0.7172 |
0.4999 | 8.0 | 904 | 1.6172 | 0.7303 |
0.1394 | 9.0 | 1017 | 1.7880 | 0.7116 |
0.1394 | 10.0 | 1130 | 1.8037 | 0.7228 |
0.1394 | 11.0 | 1243 | 1.8644 | 0.7303 |
0.1394 | 12.0 | 1356 | 1.9682 | 0.7210 |
0.1394 | 13.0 | 1469 | 2.0287 | 0.7266 |
0.0446 | 14.0 | 1582 | 2.0842 | 0.7247 |
0.0446 | 15.0 | 1695 | 2.0848 | 0.7172 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for rajevan123/STS-conventional-Fine-Tuning-Capstone-roberta-base-filtered-270
Base model
FacebookAI/roberta-base