|
--- |
|
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 |
|
|
