bart-large-finetuned-aeslc-test
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: 2.4993
- Rouge1: 34.1259
- Rouge2: 18.262
- Rougel: 33.121
- Rougelsum: 33.1402
- Gen Len: 10.1516
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: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 3.1135 | 1.0 | 980 | 2.4993 | 34.1259 | 18.262 | 33.121 | 33.1402 | 10.1516 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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