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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: summarise_v7
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_v7
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: 1.1331
- Rouge2 Precision: 0.3023
- Rouge2 Recall: 0.3298
- Rouge2 Fmeasure: 0.2949
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 1.3257 | 0.22 | 10 | 1.4084 | 0.1157 | 0.4297 | 0.1742 |
| 1.6076 | 0.44 | 20 | 1.2212 | 0.337 | 0.3337 | 0.3005 |
| 1.1881 | 0.67 | 30 | 1.2107 | 0.3219 | 0.3431 | 0.3095 |
| 1.6237 | 0.89 | 40 | 1.1331 | 0.3023 | 0.3298 | 0.2949 |
### Framework versions
- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 1.2.1
- Tokenizers 0.12.1
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