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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: 4.3552
- Bleu: 19.2576
- Gen Len: 17.7448
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 |
|---|---|---|---|---|---|
| 2.7876 | 10.31 | 1000 | 4.2606 | 15.7275 | 15.5938 |
| 0.1404 | 20.62 | 2000 | 4.2496 | 16.6706 | 17.4375 |
| 0.0398 | 30.93 | 3000 | 4.3486 | 19.2786 | 17.8385 |
| 0.0107 | 41.24 | 4000 | 4.3411 | 21.5085 | 17.2917 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
