bart-large-finetuned-aeslc
This model is a fine-tuned version of facebook/bart-large on the aeslc dataset. It achieves the following results on the evaluation set:
- Loss: 4.6657
- Rouge1: 38.0679
- Rouge2: 19.8904
- Rougel: 37.1179
- Rougelsum: 37.1066
- Gen Len: 9.1316
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.6268 | 1.0 | 7218 | 4.4738 | 36.0615 | 18.1082 | 35.2023 | 35.175 | 8.0694 |
| 1.9548 | 2.0 | 14436 | 4.4965 | 37.1784 | 19.2713 | 36.2803 | 36.2347 | 9.2699 |
| 1.4117 | 3.0 | 21654 | 4.6657 | 38.0679 | 19.8904 | 37.1179 | 37.1066 | 9.1316 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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Dataset used to train sohamchougule/bart-large-finetuned-aeslc
Evaluation results
- Rouge1 on aeslcvalidation set self-reported38.068