albert-rating-regression-rob-dset
This model is a fine-tuned version of albert/albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1105
- Accuracy: 0.5692
- Mse: 0.6352
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Mse |
|---|---|---|---|---|---|
| No log | 1.0 | 425 | 1.0055 | 0.5593 | 0.7025 |
| 1.153 | 2.0 | 850 | 1.0727 | 0.5318 | 0.7066 |
| 0.9044 | 3.0 | 1275 | 1.0269 | 0.5689 | 0.7080 |
| 0.6813 | 4.0 | 1700 | 1.1105 | 0.5692 | 0.6352 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1