---
license: mit
base_model: facebook/bart-large-xsum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: LLM_Teached_Bart
  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. -->

# LLM_Teached_Bart

This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co/facebook/bart-large-xsum) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7715
- Rouge1: 0.4781
- Rouge2: 0.2085
- Rougel: 0.3718
- Rougelsum: 0.372
- Gen Len: 41.3245

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.6623        | 1.0   | 1250 | 1.6705          | 0.4681 | 0.2057 | 0.3632 | 0.3631    | 43.4718 |
| 1.2986        | 2.0   | 2500 | 1.6330          | 0.476  | 0.2105 | 0.3732 | 0.3737    | 39.9745 |
| 1.0401        | 3.0   | 3750 | 1.7081          | 0.4792 | 0.2134 | 0.3762 | 0.3763    | 40.6155 |
| 0.8853        | 4.0   | 5000 | 1.7715          | 0.4781 | 0.2085 | 0.3718 | 0.372     | 41.3245 |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0