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This model is a fine-tuned version of mbart-large-cc25 on an custom dataset. It achieves the following results on the evaluation set:
- Loss: 3.7663
- Bleu: 19.3382
- Gen Len: 17.8929
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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 2.6161 | 11.09 | 2000 | 3.1762 | 13.5109 | 19.1966 |
| 2.6161 | 13.86 | 2500 | 3.0375 | 16.2868 | 18.7985 |
| 1.4467 | 16.62 | 3000 | 3.1328 | 17.6991 | 18.1949 |
| 1.4467 | 19.39 | 3500 | 3.2690 | 17.9052 | 18.3117 |
| 0.6809 | 22.15 | 4000 | 3.3850 | 18.4075 | 18.2149 |
| 0.6809 | 24.91 | 4500 | 3.4465 | 19.0339 | 18.009 |
| 0.3422 | 27.68 | 5000 | 3.5680 | 18.7281 | 17.5902 |
| 0.3422 | 30.44 | 5500 | 3.6350 | 19.1534 | 18.2177 |
| 0.1941 | 33.2 | 6000 | 3.7153 | 19.2575 | 17.8784 |
| 0.1941 | 35.97 | 6500 | 3.7382 | 19.2475 | 17.9831 |
| 0.1271 | 38.73 | 7000 | 3.7573 | 19.3045 | 17.9889 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
