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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: led-base-16384-biolaysum-both-with_references
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. -->
# led-base-16384-biolaysum-both-with_references
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: 2.2428
- Rouge1: 0.4562
- Rouge2: 0.1529
- Rougel: 0.2402
- Rougelsum: 0.2401
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.4777 | 0.14 | 1000 | 2.3948 | 0.4284 | 0.1431 | 0.2336 | 0.2336 |
| 2.3863 | 0.27 | 2000 | 2.3211 | 0.4455 | 0.1496 | 0.2380 | 0.2379 |
| 2.3509 | 0.41 | 3000 | 2.2809 | 0.4521 | 0.1521 | 0.2406 | 0.2406 |
| 2.3063 | 0.55 | 4000 | 2.2428 | 0.4562 | 0.1529 | 0.2402 | 0.2401 |
| 2.2754 | 0.69 | 5000 | 2.2222 | 0.4491 | 0.1506 | 0.2393 | 0.2393 |
| 2.268 | 0.82 | 6000 | 2.2113 | 0.4499 | 0.1519 | 0.2406 | 0.2405 |
| 2.2594 | 0.96 | 7000 | 2.1892 | 0.4519 | 0.1515 | 0.2390 | 0.2391 |
### Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1
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