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

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# DilaogLED-Finetuned-sum-AP

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: 0.4092
- Rouge1: 0.5362
- Rouge2: 0.2624
- Rougel: 0.3762

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 0.4612        | 1.0   | 1600 | 0.4222          | 0.5319 | 0.2612 | 0.3737 |
| 0.4007        | 2.0   | 3200 | 0.4092          | 0.5362 | 0.2624 | 0.3762 |


### Framework versions

- Transformers 4.51.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1