aia-hw231223
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: 0.7712
- Matthews Correlation: 0.5235
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: 2.3007647215162288e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 14
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|---|---|---|---|---|
| 0.4922 | 1.0 | 1069 | 0.4697 | 0.4691 |
| 0.3351 | 2.0 | 2138 | 0.6338 | 0.5118 |
| 0.2356 | 3.0 | 3207 | 0.7712 | 0.5235 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
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Model tree for zhe0/aia-hw231223
Base model
distilbert/distilbert-base-uncased