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en-it-model
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-it on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.1962
- Train Acc: 0.4204
- Validation Loss: 0.2883
- Validation Acc: 0.4046
- Epoch: 8
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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
| Train Loss | Train Acc | Validation Loss | Validation Acc | Epoch |
|---|---|---|---|---|
| 0.3407 | 0.4068 | 0.2950 | 0.4038 | 0 |
| 0.2827 | 0.4128 | 0.2846 | 0.4052 | 1 |
| 0.2563 | 0.4147 | 0.2787 | 0.4054 | 2 |
| 0.2389 | 0.4166 | 0.2777 | 0.4056 | 3 |
| 0.2262 | 0.4185 | 0.2800 | 0.4051 | 4 |
| 0.2161 | 0.4186 | 0.2817 | 0.4049 | 5 |
| 0.2082 | 0.4199 | 0.2829 | 0.4051 | 6 |
| 0.2014 | 0.4213 | 0.2860 | 0.4047 | 7 |
| 0.1962 | 0.4204 | 0.2883 | 0.4046 | 8 |
Framework versions
- Transformers 4.24.0
- TensorFlow 2.9.2
- Datasets 2.6.1
- Tokenizers 0.13.2
