---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: tl-test-learn-prompt-classifier
  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. -->

# tl-test-learn-prompt-classifier

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co./distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.2656
- Train Accuracy: 0.9728
- Validation Loss: 0.3730
- Validation Accuracy: 0.8500
- Epoch: 6

## 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 |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.6956     | 0.4728         | 0.6850          | 0.625               | 0     |
| 0.6722     | 0.6685         | 0.6670          | 0.75                | 1     |
| 0.6520     | 0.7120         | 0.6367          | 0.6875              | 2     |
| 0.6002     | 0.8261         | 0.5741          | 0.8000              | 3     |
| 0.5079     | 0.875          | 0.4797          | 0.8875              | 4     |
| 0.3805     | 0.9511         | 0.4118          | 0.8250              | 5     |
| 0.2656     | 0.9728         | 0.3730          | 0.8500              | 6     |


### Framework versions

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