work1_AIA_LLM_B_132001
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: 0.9305
- Matthews Correlation: 0.5116
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: 4.6144778537845165e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 3
- 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 |
Matthews Correlation |
No log |
1.0 |
268 |
0.4654 |
0.4612 |
0.415 |
2.0 |
536 |
0.5235 |
0.4858 |
0.415 |
3.0 |
804 |
0.6812 |
0.4887 |
0.1523 |
4.0 |
1072 |
0.8019 |
0.5029 |
0.1523 |
5.0 |
1340 |
0.9305 |
0.5116 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2