albert-albert-base-v2
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: 1.3863
- Accuracy: 0.2639
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- 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 | Accuracy |
|---|---|---|---|---|
| 1.3871 | 1.0 | 2857 | 1.3863 | 0.2752 |
| 1.3868 | 2.0 | 5714 | 1.3863 | 0.2491 |
| 1.3866 | 3.0 | 8571 | 1.3863 | 0.2639 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.0
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Model tree for daze-unlv/albert-albert-base-v2
Base model
albert/albert-base-v2