temp_assamese
This model is a fine-tuned version of microsoft/mdeberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8132
- Accuracy: 0.8287
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: 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: 1.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.4466 | 0.0931 | 5000 | 1.5004 | 0.7075 |
| 1.4994 | 0.1862 | 10000 | 1.2256 | 0.7532 |
| 1.2888 | 0.2793 | 15000 | 1.0994 | 0.7766 |
| 1.1746 | 0.3723 | 20000 | 1.0090 | 0.7915 |
| 1.0994 | 0.4654 | 25000 | 0.9514 | 0.8021 |
| 1.0379 | 0.5585 | 30000 | 0.9029 | 0.8115 |
| 0.9956 | 0.6516 | 35000 | 0.8695 | 0.8174 |
| 0.9647 | 0.7447 | 40000 | 0.8462 | 0.8216 |
| 0.9351 | 0.8378 | 45000 | 0.8274 | 0.8258 |
| 0.9194 | 0.9309 | 50000 | 0.8120 | 0.8286 |
Framework versions
- Transformers 4.43.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for pritamdeka/mDeBERTa-v3-base-Assamese
Base model
microsoft/mdeberta-v3-base