---
library_name: transformers
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: BART-Large-psychological-dataset
  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. -->

# BART-Large-psychological-dataset

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co./facebook/bart-large-cnn) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1549
- Rouge1: 0.6621
- Rouge2: 0.4488
- Rougel: 0.5658
- Rougelsum: 0.5656
- Gen Len: 80.6204

## 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: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 274  | 0.8651          | 0.6252 | 0.3953 | 0.5206 | 0.5206    | 86.9982 |
| 0.7484        | 2.0   | 548  | 0.8332          | 0.648  | 0.4301 | 0.554  | 0.5541    | 79.885  |
| 0.7484        | 3.0   | 822  | 0.8943          | 0.6498 | 0.4335 | 0.5514 | 0.5518    | 82.635  |
| 0.3207        | 4.0   | 1096 | 0.9653          | 0.6571 | 0.4422 | 0.5607 | 0.5609    | 79.9708 |
| 0.3207        | 5.0   | 1370 | 1.0514          | 0.6582 | 0.4445 | 0.5637 | 0.5639    | 79.8047 |
| 0.1557        | 6.0   | 1644 | 1.0752          | 0.6607 | 0.4476 | 0.5659 | 0.5657    | 79.6058 |
| 0.1557        | 7.0   | 1918 | 1.1302          | 0.6588 | 0.4443 | 0.5626 | 0.5626    | 80.5821 |
| 0.0845        | 8.0   | 2192 | 1.1549          | 0.6621 | 0.4488 | 0.5658 | 0.5656    | 80.6204 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1