model_te
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: 1.0733
- Matthews Correlation: 0.5324
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: 16
- eval_batch_size: 16
- 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 | Matthews Correlation |
|---|---|---|---|---|
| 0.1729 | 1.0 | 535 | 0.6953 | 0.5007 |
| 0.1152 | 2.0 | 1070 | 0.9441 | 0.5200 |
| 0.0809 | 3.0 | 1605 | 0.9402 | 0.5150 |
| 0.1009 | 4.0 | 2140 | 1.0245 | 0.5297 |
| 0.0797 | 5.0 | 2675 | 1.0733 | 0.5324 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.20.0
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Inference Providers
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Model tree for alexlawtengyi/model_te
Base model
distilbert/distilbert-base-uncased