---
library_name: transformers
license: mit
base_model: facebook/bart-large-mnli
tags:
- generated_from_keras_callback
model-index:
- name: zero-shot-prompt-classifier-bart-ft
  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. -->

# zero-shot-prompt-classifier-bart-ft

This model is a fine-tuned version of [facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.4474
- Train Accuracy: 0.7843
- Validation Loss: 1.5942
- Validation Accuracy: 0.4657
- Epoch: 4

## 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: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': 5e-06, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.9969     | 0.5490         | 0.9182          | 0.6225              | 0     |
| 0.7647     | 0.6601         | 1.0025          | 0.5441              | 1     |
| 0.6465     | 0.7157         | 1.1472          | 0.5392              | 2     |
| 0.5849     | 0.7418         | 1.1974          | 0.5049              | 3     |
| 0.4474     | 0.7843         | 1.5942          | 0.4657              | 4     |


### Framework versions

- Transformers 4.44.2
- TensorFlow 2.18.0-dev20240717
- Datasets 2.21.0
- Tokenizers 0.19.1