---
license: apache-2.0
base_model: ainize/bart-base-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-base-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-base-cnn-YT-transcript-sum

This model is a fine-tuned version of [ainize/bart-base-cnn](https://huggingface.co/ainize/bart-base-cnn) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4969
- Rouge1: 27.1516
- Rouge2: 14.6227
- Rougel: 23.3968
- Rougelsum: 25.4786
- Gen Len: 19.9954

## 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: 4
- eval_batch_size: 4
- 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   | 216  | 1.5374          | 24.7307 | 11.5124 | 20.6823 | 22.9189   | 19.9630 |
| No log        | 2.0   | 432  | 1.4976          | 26.825  | 14.0512 | 23.2078 | 25.2044   | 19.9583 |
| 1.5449        | 3.0   | 648  | 1.4969          | 27.1516 | 14.6227 | 23.3968 | 25.4786   | 19.9954 |
| 1.5449        | 4.0   | 864  | 1.5345          | 27.2526 | 15.0873 | 23.8556 | 25.7798   | 19.9861 |
| 0.9           | 5.0   | 1080 | 1.5962          | 26.8267 | 14.7267 | 23.2263 | 25.2149   | 19.9676 |
| 0.9           | 6.0   | 1296 | 1.6378          | 26.8444 | 14.8753 | 23.254  | 25.2943   | 19.9815 |
| 0.5749        | 7.0   | 1512 | 1.6819          | 27.1776 | 14.898  | 23.2454 | 25.4298   | 19.9583 |
| 0.5749        | 8.0   | 1728 | 1.7360          | 26.9518 | 15.308  | 23.6574 | 25.2991   | 19.9769 |
| 0.5749        | 9.0   | 1944 | 1.7796          | 27.9253 | 15.7998 | 24.4827 | 26.4424   | 19.9769 |
| 0.3668        | 10.0  | 2160 | 1.8078          | 26.9211 | 15.0903 | 23.4484 | 25.4369   | 19.9815 |
| 0.3668        | 11.0  | 2376 | 1.8405          | 27.4434 | 15.3608 | 23.903  | 25.8117   | 19.9861 |
| 0.255         | 12.0  | 2592 | 1.8447          | 27.7175 | 15.7173 | 24.2096 | 26.0946   | 19.9815 |
| 0.255         | 13.0  | 2808 | 1.8834          | 27.2409 | 15.3865 | 23.7314 | 25.7682   | 19.9815 |
| 0.192         | 14.0  | 3024 | 1.8796          | 27.2939 | 15.5502 | 23.8294 | 25.7409   | 19.9815 |
| 0.192         | 15.0  | 3240 | 1.8851          | 27.6741 | 15.771  | 24.1976 | 26.1196   | 19.9722 |


### Framework versions

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