rubert-tiny2-1-4
This model is a fine-tuned version of cointegrated/rubert-tiny2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3882
- Accuracy: 0.9001
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: 1e-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: 500
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.9597 | 1.0 | 1500 | 1.1052 | 0.7613 |
| 0.9583 | 2.0 | 3000 | 0.8140 | 0.8157 |
| 0.7343 | 3.0 | 4500 | 0.6514 | 0.8502 |
| 0.6076 | 4.0 | 6000 | 0.5656 | 0.867 |
| 0.5257 | 5.0 | 7500 | 0.5115 | 0.8771 |
| 0.4694 | 6.0 | 9000 | 0.4748 | 0.8826 |
| 0.4296 | 7.0 | 10500 | 0.4477 | 0.8885 |
| 0.4006 | 8.0 | 12000 | 0.4295 | 0.8938 |
| 0.3753 | 9.0 | 13500 | 0.4159 | 0.896 |
| 0.358 | 10.0 | 15000 | 0.4066 | 0.8979 |
| 0.3417 | 11.0 | 16500 | 0.3994 | 0.8992 |
| 0.3296 | 12.0 | 18000 | 0.3943 | 0.8993 |
| 0.3203 | 13.0 | 19500 | 0.3914 | 0.8993 |
| 0.3158 | 14.0 | 21000 | 0.3889 | 0.9001 |
| 0.3126 | 15.0 | 22500 | 0.3882 | 0.9001 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
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Base model
cointegrated/rubert-tiny2