---
library_name: transformers
license: apache-2.0
base_model: sshleifer/distilbart-xsum-6-6
tags:
- generated_from_trainer
model-index:
- name: distilbart-summarization-base
  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. -->

# distilbart-summarization-base

This model is a fine-tuned version of [sshleifer/distilbart-xsum-6-6](https://huggingface.co/sshleifer/distilbart-xsum-6-6) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2566

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAFACTOR and the args are:
No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.699         | 0.1882 | 500  | 2.5648          |
| 2.5321        | 0.3764 | 1000 | 2.4413          |
| 2.4701        | 0.5645 | 1500 | 2.3791          |
| 2.4213        | 0.7527 | 2000 | 2.3353          |
| 2.404         | 0.9409 | 2500 | 2.3089          |
| 2.3352        | 1.1291 | 3000 | 2.2903          |
| 2.2998        | 1.3173 | 3500 | 2.2765          |
| 2.2999        | 1.5055 | 4000 | 2.2673          |
| 2.2665        | 1.6936 | 4500 | 2.2611          |
| 2.3412        | 1.8818 | 5000 | 2.2566          |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0