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---
library_name: transformers
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: small-dataset-factor
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. -->
# small-dataset-factor
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: 1.0342
- Rouge1: 0.7004
- Rouge2: 0.5624
- Rougel: 0.5489
- Rougelsum: 0.5489
- Gen Len: 72.0
## 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 | 1 | 1.4501 | 0.5989 | 0.3974 | 0.493 | 0.493 | 61.5 |
| No log | 2.0 | 2 | 1.4501 | 0.5989 | 0.3974 | 0.493 | 0.493 | 61.5 |
| No log | 3.0 | 3 | 1.2372 | 0.6418 | 0.459 | 0.5287 | 0.5287 | 66.5 |
| No log | 4.0 | 4 | 1.1366 | 0.6293 | 0.4495 | 0.5183 | 0.5183 | 68.0 |
| No log | 5.0 | 5 | 1.0768 | 0.6763 | 0.5432 | 0.5941 | 0.5941 | 75.0 |
| No log | 6.0 | 6 | 1.0550 | 0.6846 | 0.5503 | 0.5357 | 0.5357 | 74.0 |
| No log | 7.0 | 7 | 1.0425 | 0.6846 | 0.5503 | 0.5357 | 0.5357 | 74.0 |
| No log | 8.0 | 8 | 1.0342 | 0.7004 | 0.5624 | 0.5489 | 0.5489 | 72.0 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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