---
license: apache-2.0
base_model: facebook/bart-large
tags:
- generated_from_trainer
metrics:
- rouge
- precision
- recall
- f1
model-index:
- name: LLM_Teached_Bart_From_Scratch
  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_From_Scratch

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: 1.4999
- Rouge1: 0.4331
- Rouge2: 0.2164
- Rougel: 0.3724
- Rougelsum: 0.3725
- Gen Len: 19.9255
- Precision: 0.9125
- Recall: 0.8885
- F1: 0.9002

## 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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:---------:|:------:|:------:|
| No log        | 1.0   | 390  | 1.5709          | 0.4119 | 0.2002 | 0.3529 | 0.3527    | 19.9709 | 0.9093    | 0.8846 | 0.8966 |
| 1.8155        | 2.0   | 781  | 1.5361          | 0.4331 | 0.2157 | 0.3717 | 0.3717    | 19.9185 | 0.9123    | 0.8889 | 0.9003 |
| 1.5875        | 3.0   | 1172 | 1.5030          | 0.4263 | 0.2129 | 0.3671 | 0.3673    | 19.9545 | 0.9117    | 0.8871 | 0.899  |
| 1.4978        | 3.99  | 1560 | 1.4999          | 0.4331 | 0.2164 | 0.3724 | 0.3725    | 19.9255 | 0.9125    | 0.8885 | 0.9002 |


### Framework versions

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