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farsi_lastname_classifier_4
This model is a fine-tuned version of microsoft/deberta-v3-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2337
- Accuracy: 0.96
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: 0.0001
- train_batch_size: 128
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 12 | 0.5673 | 0.836 |
| No log | 2.0 | 24 | 0.4052 | 0.868 |
| No log | 3.0 | 36 | 0.2211 | 0.932 |
| No log | 4.0 | 48 | 0.2488 | 0.926 |
| No log | 5.0 | 60 | 0.1490 | 0.954 |
| No log | 6.0 | 72 | 0.1464 | 0.968 |
| No log | 7.0 | 84 | 0.1923 | 0.954 |
| No log | 8.0 | 96 | 0.2070 | 0.96 |
| No log | 9.0 | 108 | 0.2055 | 0.962 |
| No log | 10.0 | 120 | 0.2436 | 0.942 |
| No log | 11.0 | 132 | 0.2173 | 0.96 |
| No log | 12.0 | 144 | 0.2342 | 0.956 |
| No log | 13.0 | 156 | 0.2337 | 0.962 |
| No log | 14.0 | 168 | 0.2332 | 0.96 |
| No log | 15.0 | 180 | 0.2337 | 0.96 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2
