AlbertResults2
This model is a fine-tuned version of albert-base-v2 on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.1619
- Accuracy: 0.931
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: 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3348 | 1.0 | 1000 | 0.2663 | 0.9075 |
| 0.1566 | 2.0 | 2000 | 0.1619 | 0.931 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2