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---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: video_transcript_summary
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. -->
# video_transcript_summary
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: 5.5472
- Rouge1: 0.3909
- Rouge2: 0.1328
- Rougel: 0.2802
- Rougelsum: 0.2801
- Gen Len: 69.8235
## 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: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 5 | 2.6381 | 0.3163 | 0.0838 | 0.2135 | 0.2138 | 72.1176 |
| No log | 2.0 | 10 | 2.4739 | 0.345 | 0.0969 | 0.2372 | 0.2364 | 69.7647 |
| No log | 3.0 | 15 | 2.6011 | 0.3719 | 0.116 | 0.2619 | 0.2605 | 69.7059 |
| No log | 4.0 | 20 | 2.7476 | 0.3769 | 0.1156 | 0.2588 | 0.2572 | 72.9412 |
| No log | 5.0 | 25 | 2.9283 | 0.3812 | 0.1206 | 0.2645 | 0.2625 | 74.4706 |
| No log | 6.0 | 30 | 3.3089 | 0.3722 | 0.1194 | 0.2779 | 0.2769 | 70.1765 |
| No log | 7.0 | 35 | 3.6585 | 0.3802 | 0.1177 | 0.2718 | 0.2719 | 73.2941 |
| No log | 8.0 | 40 | 3.8924 | 0.3764 | 0.1056 | 0.2661 | 0.2651 | 70.8235 |
| No log | 9.0 | 45 | 4.3638 | 0.3677 | 0.1144 | 0.2653 | 0.2634 | 74.0 |
| No log | 10.0 | 50 | 4.5590 | 0.354 | 0.1069 | 0.2491 | 0.2477 | 71.0 |
| No log | 11.0 | 55 | 4.5746 | 0.4103 | 0.1359 | 0.2935 | 0.293 | 72.5882 |
| No log | 12.0 | 60 | 4.9055 | 0.3869 | 0.118 | 0.2705 | 0.2695 | 66.1176 |
| No log | 13.0 | 65 | 5.0987 | 0.3947 | 0.1292 | 0.2713 | 0.2716 | 74.7647 |
| No log | 14.0 | 70 | 5.3199 | 0.3814 | 0.1135 | 0.2839 | 0.2816 | 72.2353 |
| No log | 15.0 | 75 | 5.4462 | 0.4092 | 0.1265 | 0.2896 | 0.29 | 68.0 |
| No log | 16.0 | 80 | 5.4262 | 0.412 | 0.1282 | 0.293 | 0.2932 | 72.0 |
| No log | 17.0 | 85 | 5.4873 | 0.3776 | 0.1051 | 0.2637 | 0.2636 | 68.8824 |
| No log | 18.0 | 90 | 5.6043 | 0.3932 | 0.1106 | 0.2734 | 0.2727 | 67.9412 |
| No log | 19.0 | 95 | 5.7495 | 0.3694 | 0.1075 | 0.2699 | 0.2692 | 69.7647 |
| No log | 20.0 | 100 | 5.6518 | 0.3849 | 0.1109 | 0.2714 | 0.2709 | 65.5882 |
| No log | 21.0 | 105 | 5.4524 | 0.3762 | 0.1101 | 0.2598 | 0.2596 | 64.5294 |
| No log | 22.0 | 110 | 5.5472 | 0.3909 | 0.1328 | 0.2802 | 0.2801 | 69.8235 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
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