---
license: apache-2.0
base_model: allenai/led-base-16384
tags:
- generated_from_trainer
model-index:
- name: led_large_16384_docstring
  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_large_16384_docstring

This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/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