MiniLMv2-L12-H384-emotion
This model is a fine-tuned version of nreimers/MiniLMv2-L12-H384-distilled-from-RoBERTa-Large on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2069
- Accuracy: 0.925
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: 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: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Accuracy |
| 0.8745 |
1.0 |
1000 |
0.6673 |
0.81 |
| 0.3466 |
2.0 |
2000 |
0.2816 |
0.918 |
| 0.2201 |
3.0 |
3000 |
0.2367 |
0.9215 |
| 0.1761 |
4.0 |
4000 |
0.2069 |
0.925 |
| 0.1435 |
5.0 |
5000 |
0.2089 |
0.922 |
| 0.1454 |
6.0 |
6000 |
0.2168 |
0.923 |
| 0.1041 |
7.0 |
7000 |
0.2081 |
0.924 |
| 0.0953 |
8.0 |
8000 |
0.2133 |
0.9245 |
Framework versions
- Transformers 4.12.3
- Pytorch 1.9.1
- Datasets 1.15.1
- Tokenizers 0.10.3
