distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2148
- Accuracy: 0.926
- F1: 0.9261
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: 64
- eval_batch_size: 64
- 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 |
F1 |
| 0.8297 |
1.0 |
250 |
0.3235 |
0.9015 |
0.8977 |
| 0.2504 |
2.0 |
500 |
0.2148 |
0.926 |
0.9261 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.7.1
- Datasets 2.3.2
- Tokenizers 0.12.1
