Result_Model
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: 0.3362
- Accuracy: 0.8353
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 | Accuracy |
---|---|---|---|---|
0.4662 | 1.0 | 7569 | 0.4709 | 0.75 |
0.3854 | 2.0 | 15138 | 0.4060 | 0.7979 |
0.3492 | 3.0 | 22707 | 0.3570 | 0.8174 |
0.3205 | 4.0 | 30276 | 0.3372 | 0.8304 |
0.2968 | 5.0 | 37845 | 0.3362 | 0.8353 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for ArchitJamb/Result_Model
Base model
distilbert/distilbert-base-uncased