metadata
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: summarise_v6
results: []
summarise_v6
This model is a fine-tuned version of allenai/led-base-16384 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0781
- Rouge2 Precision: 0.3575
- Rouge2 Recall: 0.2677
- Rouge2 Fmeasure: 0.2899
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
- 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 |
|---|---|---|---|---|---|---|
| 1.735 | 0.22 | 10 | 1.3561 | 0.1706 | 0.4851 | 0.2442 |
| 1.8028 | 0.44 | 20 | 1.1805 | 0.3464 | 0.2786 | 0.2879 |
| 1.2608 | 0.67 | 30 | 1.1217 | 0.3634 | 0.309 | 0.3006 |
| 1.5478 | 0.89 | 40 | 1.0781 | 0.3575 | 0.2677 | 0.2899 |
Framework versions
- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 1.2.1
- Tokenizers 0.12.1