allenai/led-base-16384
This model is a fine-tuned version of allenai/led-base-16384 on the scientific_papers dataset. It achieves the following results on the evaluation set:
- Loss: 2.7667
- Rouge2 Precision: 0.15
- Rouge2 Recall: 0.0913
- Rouge2 Fmeasure: 0.1075
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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 | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 2.8931 | 0.32 | 10 | 2.9211 | 0.1243 | 0.1206 | 0.1119 |
| 3.0026 | 0.64 | 20 | 2.8150 | 0.1589 | 0.1102 | 0.1241 |
| 2.7651 | 0.96 | 30 | 2.7667 | 0.15 | 0.0913 | 0.1075 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0
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