metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-base-sst-2-64-13-30
results: []
roberta-base-sst-2-64-13-30
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6400
- Accuracy: 0.8984
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: 1.5e-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
- lr_scheduler_warmup_steps: 5
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 4 | 0.6936 | 0.5 |
| No log | 2.0 | 8 | 0.6928 | 0.5156 |
| 0.6938 | 3.0 | 12 | 0.6921 | 0.6328 |
| 0.6938 | 4.0 | 16 | 0.6911 | 0.6328 |
| 0.6895 | 5.0 | 20 | 0.6894 | 0.5859 |
| 0.6895 | 6.0 | 24 | 0.6866 | 0.625 |
| 0.6895 | 7.0 | 28 | 0.6818 | 0.6641 |
| 0.6758 | 8.0 | 32 | 0.6727 | 0.6953 |
| 0.6758 | 9.0 | 36 | 0.6495 | 0.7656 |
| 0.615 | 10.0 | 40 | 0.5773 | 0.8125 |
| 0.615 | 11.0 | 44 | 0.4229 | 0.875 |
| 0.615 | 12.0 | 48 | 0.3311 | 0.8906 |
| 0.3514 | 13.0 | 52 | 0.3047 | 0.8906 |
| 0.3514 | 14.0 | 56 | 0.3420 | 0.8828 |
| 0.0929 | 15.0 | 60 | 0.4113 | 0.8906 |
| 0.0929 | 16.0 | 64 | 0.4550 | 0.8906 |
| 0.0929 | 17.0 | 68 | 0.5299 | 0.8906 |
| 0.0206 | 18.0 | 72 | 0.6554 | 0.8594 |
| 0.0206 | 19.0 | 76 | 0.7213 | 0.8594 |
| 0.007 | 20.0 | 80 | 0.7860 | 0.8516 |
| 0.007 | 21.0 | 84 | 0.8466 | 0.8438 |
| 0.007 | 22.0 | 88 | 0.8522 | 0.8516 |
| 0.0037 | 23.0 | 92 | 0.8023 | 0.8516 |
| 0.0037 | 24.0 | 96 | 0.6670 | 0.8828 |
| 0.0028 | 25.0 | 100 | 0.6224 | 0.8984 |
| 0.0028 | 26.0 | 104 | 0.6283 | 0.8906 |
| 0.0028 | 27.0 | 108 | 0.6333 | 0.8906 |
| 0.0026 | 28.0 | 112 | 0.6307 | 0.8906 |
| 0.0026 | 29.0 | 116 | 0.6348 | 0.8984 |
| 0.003 | 30.0 | 120 | 0.6400 | 0.8984 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.4.0
- Tokenizers 0.13.3