emotion-analysis-3000
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3205
- Accuracy: 0.9015
- F1: 0.9014
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: 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: 5
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Accuracy |
F1 |
| No log |
1.0 |
233 |
0.2691 |
0.9070 |
0.9068 |
| No log |
2.0 |
466 |
0.2963 |
0.8928 |
0.8922 |
| 0.2332 |
3.0 |
699 |
0.3205 |
0.9015 |
0.9014 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
