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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: 3.4005
- Bleu: 26.0229
- Gen Len: 15.1659
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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 4.5769 | 1.15 | 1000 | 4.0805 | 14.9483 | 30.0618 |
| 2.8098 | 2.31 | 2000 | 3.0612 | 19.7963 | 16.7121 |
| 1.7974 | 3.46 | 3000 | 2.8258 | 21.7059 | 15.5179 |
| 1.1474 | 4.62 | 4000 | 2.6951 | 22.4801 | 16.6382 |
| 0.8042 | 5.77 | 5000 | 2.7272 | 22.4419 | 15.1393 |
| 0.5605 | 6.93 | 6000 | 2.8239 | 23.1096 | 15.6457 |
| 0.3857 | 8.08 | 7000 | 2.9448 | 24.2536 | 15.1538 |
| ... | |||||
| 0.0042 | 40.42 | 35000 | 3.3485 | 25.2464 | 15.2387 |
| 0.0029 | 41.57 | 36000 | 3.3744 | 25.2885 | 15.1306 |
| 0.0026 | 42.73 | 37000 | 3.3947 | 25.9359 | 15.1896 |
| 0.0024 | 43.88 | 38000 | 3.3699 | 25.5309 | 15.2671 |
| 0.0022 | 45.03 | 39000 | 3.3947 | 25.2932 | 15.1387 |
| 0.0011 | 46.19 | 40000 | 3.4075 | 25.7551 | 15.1231 |
| 0.001 | 47.34 | 41000 | 3.3918 | 25.6345 | 15.1243 |
| 0.0007 | 48.5 | 42000 | 3.4063 | 25.7209 | 15.111 |
| 0.0006 | 49.65 | 43000 | 3.4003 | 25.9227 | 15.1873 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
