---
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: 1.8314
- Rouge1: 0.4852
- Rouge2: 0.2152
- Rougel: 0.3758
- Rougelsum: 0.3758
- Gen Len: 44.2945

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.7164        | 1.0   | 625  | 1.7203          | 0.4723 | 0.209  | 0.3674 | 0.3668    | 44.1491 |
| 1.3424        | 2.0   | 1250 | 1.6998          | 0.484  | 0.2166 | 0.37   | 0.3695    | 45.3727 |
| 1.1171        | 3.0   | 1875 | 1.7546          | 0.4824 | 0.2144 | 0.3728 | 0.3728    | 43.7636 |
| 0.8193        | 4.0   | 2500 | 1.8314          | 0.4852 | 0.2152 | 0.3758 | 0.3758    | 44.2945 |


### Framework versions

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