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
- Downloads last month
- 4
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for juraj-juraj/led_base_16384_docstring
Base model
allenai/led-base-16384