led_large_16384_docstring
This model is a fine-tuned version of allenai/led-base-16384 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4572
- Rouge2 Precision: 0.091
- Rouge2 Recall: 0.2244
- Rouge2 Fmeasure: 0.1219
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
- lr_scheduler_warmup_steps: 1500
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 1.099 | 1.33 | 5000 | 1.5197 | 0.0898 | 0.22 | 0.1202 |
| 0.9149 | 2.67 | 10000 | 1.4572 | 0.091 | 0.2244 | 0.1219 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.5
- Tokenizers 0.15.2
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