---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_keras_callback
model-index:
- name: s-man2099/fb-bart-large-cnn-3k
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# s-man2099/fb-bart-large-cnn-3k

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co./facebook/bart-large-cnn) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.7614
- Validation Loss: 5.2124
- Epoch: 7

## 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:
- optimizer: {'inner_optimizer': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5.6e-05, 'decay_steps': 7712, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}, 'registered_name': 'AdamWeightDecay'}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 3.5321     | 3.5283          | 0     |
| 2.9850     | 3.5282          | 1     |
| 2.4341     | 3.6583          | 2     |
| 1.9282     | 4.0282          | 3     |
| 1.4829     | 4.3616          | 4     |
| 1.1386     | 4.7411          | 5     |
| 0.9013     | 5.1059          | 6     |
| 0.7614     | 5.2124          | 7     |


### Framework versions

- Transformers 4.34.1
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.14.1