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library_name: transformers
license: apache-2.0
base_model: sshleifer/distilbart-xsum-6-6
tags:
- generated_from_trainer
model-index:
- name: distilbart-summarization-base-fulllayers
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-fulllayers
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: 1.8165
## 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: 3e-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 |
|:-------------:|:------:|:----:|:---------------:|
| 2.1052 | 0.1882 | 500 | 2.0091 |
| 1.987 | 0.3764 | 1000 | 1.9407 |
| 1.9688 | 0.5645 | 1500 | 1.9045 |
| 1.9299 | 0.7527 | 2000 | 1.8716 |
| 1.9114 | 0.9409 | 2500 | 1.8527 |
| 1.72 | 1.1291 | 3000 | 1.8458 |
| 1.6935 | 1.3173 | 3500 | 1.8364 |
| 1.6997 | 1.5055 | 4000 | 1.8282 |
| 1.6546 | 1.6936 | 4500 | 1.8212 |
| 1.7309 | 1.8818 | 5000 | 1.8165 |
### Framework versions
- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
|