---
library_name: transformers
base_model: MingZhong/DialogLED-base-16384
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: LED-Finetuned-sum-full-note
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# LED-Finetuned-sum-full-note

This model is a fine-tuned version of [MingZhong/DialogLED-base-16384](https://huggingface.co/MingZhong/DialogLED-base-16384) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7979
- Rouge1: 0.4228
- Rouge2: 0.2722
- Rougel: 0.3218

## 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 0.864         | 1.0   | 1600 | 0.8257          | 0.4202 | 0.2695 | 0.3197 |
| 0.7586        | 2.0   | 3200 | 0.7979          | 0.4228 | 0.2722 | 0.3218 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1