---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-YT-transcript-sum
  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-cnn-YT-transcript-sum

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4849
- Rouge1: 48.0422
- Rouge2: 22.8938
- Rougel: 34.0775
- Rougelsum: 44.7056
- Gen Len: 108.8009

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| No log        | 1.0   | 432  | 1.5362          | 49.0506 | 22.9422 | 35.5667 | 45.7219   | 88.0602  |
| 1.5312        | 2.0   | 864  | 1.4849          | 48.0422 | 22.8938 | 34.0775 | 44.7056   | 108.8009 |
| 0.9026        | 3.0   | 1296 | 1.5761          | 50.0558 | 23.9657 | 36.247  | 46.4508   | 96.0231  |
| 0.5642        | 4.0   | 1728 | 1.8304          | 50.6862 | 24.4638 | 36.3568 | 47.2607   | 93.1667  |
| 0.3629        | 5.0   | 2160 | 1.9355          | 51.2362 | 25.1077 | 37.772  | 47.4362   | 88.9583  |
| 0.2335        | 6.0   | 2592 | 2.1215          | 49.5831 | 23.4294 | 35.9861 | 45.9306   | 94.2917  |
| 0.1603        | 7.0   | 3024 | 2.2890          | 49.8716 | 23.4756 | 36.2617 | 46.2866   | 88.7639  |
| 0.1603        | 8.0   | 3456 | 2.3604          | 49.5627 | 23.6399 | 35.9596 | 45.7914   | 88.8333  |
| 0.1049        | 9.0   | 3888 | 2.5252          | 50.358  | 24.1986 | 36.5297 | 46.5519   | 90.5463  |
| 0.0744        | 10.0  | 4320 | 2.6694          | 50.46   | 24.1493 | 37.0205 | 46.8988   | 91.0139  |
| 0.049         | 11.0  | 4752 | 2.7840          | 50.8805 | 24.5482 | 36.5901 | 46.9176   | 90.8380  |
| 0.0312        | 12.0  | 5184 | 2.8330          | 50.4793 | 24.6444 | 37.2087 | 46.7151   | 86.9444  |
| 0.0156        | 13.0  | 5616 | 2.9540          | 50.3911 | 24.4843 | 36.8037 | 46.8691   | 94.9352  |
| 0.0083        | 14.0  | 6048 | 3.0214          | 51.0557 | 25.127  | 37.1368 | 47.3072   | 92.5787  |
| 0.0083        | 15.0  | 6480 | 3.0340          | 51.3998 | 25.5847 | 37.5635 | 47.7132   | 90.5602  |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3