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mt5-small-v8-sum-fine-tuned
This model is a fine-tuned version of abdalrahmanshahrour/AraBART-summ on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 1.6114
- Epoch: 29
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 | Epoch |
|---|---|
| 2.4132 | 0 |
| 2.4084 | 1 |
| 2.3948 | 2 |
| 2.3715 | 3 |
| 2.3110 | 4 |
| 2.2797 | 5 |
| 2.2699 | 6 |
| 2.2320 | 7 |
| 2.1178 | 8 |
| 2.1323 | 9 |
| 2.0598 | 10 |
| 2.1086 | 11 |
| 2.0487 | 12 |
| 1.9561 | 13 |
| 2.0067 | 14 |
| 1.8801 | 15 |
| 1.9177 | 16 |
| 1.9594 | 17 |
| 1.8946 | 18 |
| 1.8057 | 19 |
| 1.7603 | 20 |
| 1.7916 | 21 |
| 1.7090 | 22 |
| 1.7502 | 23 |
| 1.7377 | 24 |
| 1.7007 | 25 |
| 1.6427 | 26 |
| 1.6352 | 27 |
| 1.6317 | 28 |
| 1.6114 | 29 |
Framework versions
- Transformers 4.30.2
- TensorFlow 2.13.0
- Datasets 2.13.1
- Tokenizers 0.13.3
