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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: summarise_v6
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# summarise_v6
This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/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
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