fine_tuned_model_2
This model is a fine-tuned version of albert/albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1628
- Accuracy: 0.9550
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 |
|---|---|---|---|---|
| No log | 1.0 | 28 | 0.4061 | 0.9279 |
| No log | 2.0 | 56 | 0.2302 | 0.9550 |
| No log | 3.0 | 84 | 0.1830 | 0.9640 |
| No log | 4.0 | 112 | 0.1639 | 0.9550 |
| No log | 5.0 | 140 | 0.1628 | 0.9550 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for KalaiselvanD/fine_tuned_model_2
Base model
albert/albert-base-v2