---
license: apache-2.0
base_model: facebook/bart-large
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](https://huggingface.co./facebook/bart-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6728
- Rouge1: 0.3966
- Rouge2: 0.1905
- Rougel: 0.3321
- Rougelsum: 0.3322
- Gen Len: 19.9855

## 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: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.851         | 1.0   | 1250  | 1.6235          | 0.3808 | 0.1775 | 0.3177 | 0.318     | 19.9855 |
| 1.5876        | 2.0   | 2500  | 1.5937          | 0.389  | 0.1866 | 0.3271 | 0.3274    | 19.9782 |
| 1.3922        | 3.0   | 3750  | 1.5800          | 0.3899 | 0.182  | 0.3244 | 0.3246    | 19.9918 |
| 1.2551        | 4.0   | 5000  | 1.6044          | 0.3852 | 0.1854 | 0.3223 | 0.3227    | 19.9982 |
| 1.1329        | 5.0   | 6250  | 1.6191          | 0.3978 | 0.1923 | 0.3342 | 0.3344    | 19.9855 |
| 1.042         | 6.0   | 7500  | 1.6453          | 0.3956 | 0.192  | 0.3333 | 0.3335    | 19.9864 |
| 0.9665        | 7.0   | 8750  | 1.6554          | 0.3945 | 0.1898 | 0.331  | 0.3312    | 19.9909 |
| 0.9206        | 8.0   | 10000 | 1.6728          | 0.3966 | 0.1905 | 0.3321 | 0.3322    | 19.9855 |


### Framework versions

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