BART-large-cnn-V3 / README.md
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---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
model-index:
- name: BART-large-cnn-V3
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-V3
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset.
## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| No log | 0.99 | 62 | 0.6047 | 55.4094 | 37.7224 | 45.4045 | 53.4439 | 139.8044 |
### Framework versions
- Transformers 4.35.2
- Pytorch 1.12.1
- Datasets 2.15.0
- Tokenizers 0.15.0