---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: BARTModel_ExerciseLog
  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. -->

# BARTModel_ExerciseLog

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.3574
- Rouge1: 0.8531
- Rouge2: 0.581
- Rougel: 0.8531
- Rougelsum: 0.8531
- Gen Len: 7.2857

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 18

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 2    | 7.5886          | 0.4437 | 0.1117 | 0.4458 | 0.4459    | 16.5714 |
| No log        | 2.0   | 4    | 6.4463          | 0.4127 | 0.1117 | 0.4136 | 0.4155    | 16.0    |
| No log        | 3.0   | 6    | 5.9474          | 0.5136 | 0.0952 | 0.5102 | 0.5204    | 8.2857  |
| No log        | 4.0   | 8    | 5.6884          | 0.5537 | 0.2381 | 0.5459 | 0.5459    | 8.0     |
| No log        | 5.0   | 10   | 5.5303          | 0.55   | 0.2381 | 0.5452 | 0.5452    | 6.5714  |
| No log        | 6.0   | 12   | 5.4149          | 0.55   | 0.2381 | 0.5452 | 0.5452    | 6.7143  |
| No log        | 7.0   | 14   | 5.2489          | 0.5286 | 0.2    | 0.5197 | 0.5197    | 7.0     |
| No log        | 8.0   | 16   | 5.0956          | 0.5388 | 0.2    | 0.5286 | 0.5286    | 7.0     |
| No log        | 9.0   | 18   | 4.9528          | 0.5388 | 0.2    | 0.5286 | 0.5286    | 7.0     |
| No log        | 10.0  | 20   | 4.8291          | 0.5388 | 0.2    | 0.5286 | 0.5286    | 7.1429  |
| No log        | 11.0  | 22   | 4.7158          | 0.5748 | 0.2714 | 0.567  | 0.5667    | 7.4286  |
| No log        | 12.0  | 24   | 4.6173          | 0.7388 | 0.3429 | 0.7388 | 0.7388    | 7.2857  |
| No log        | 13.0  | 26   | 4.5333          | 0.8531 | 0.581  | 0.8531 | 0.8531    | 7.2857  |
| No log        | 14.0  | 28   | 4.4660          | 0.8531 | 0.581  | 0.8531 | 0.8531    | 7.2857  |
| No log        | 15.0  | 30   | 4.4177          | 0.8531 | 0.581  | 0.8531 | 0.8531    | 7.2857  |
| No log        | 16.0  | 32   | 4.3857          | 0.8531 | 0.581  | 0.8531 | 0.8531    | 7.2857  |
| No log        | 17.0  | 34   | 4.3660          | 0.8531 | 0.581  | 0.8531 | 0.8531    | 7.2857  |
| No log        | 18.0  | 36   | 4.3574          | 0.8531 | 0.581  | 0.8531 | 0.8531    | 7.2857  |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1