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mbart-large-50-finetuned-ua-gec-2.1
This model is a fine-tuned version of facebook/mbart-large-50 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5376
- Rouge1: 18.2963
- Rouge2: 10.2365
- Rougel: 18.2593
- Rougelsum: 18.2759
- Gen Len: 28.6107
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.0765 | 1.0 | 1010 | 0.4070 | 18.2963 | 10.2365 | 18.2593 | 18.2759 | 28.522 |
| 0.046 | 2.0 | 2020 | 0.4710 | 18.2963 | 10.2365 | 18.2593 | 18.2759 | 28.578 |
| 0.0291 | 3.0 | 3030 | 0.4885 | 18.2833 | 10.2052 | 18.2454 | 18.263 | 28.5793 |
| 0.0188 | 4.0 | 4040 | 0.5145 | 18.2963 | 10.2365 | 18.2593 | 18.2759 | 28.6127 |
| 0.0117 | 5.0 | 5050 | 0.5376 | 18.2963 | 10.2365 | 18.2593 | 18.2759 | 28.6107 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
