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---

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: 0.0934
- Train Accuracy: 0.9923
- Validation Loss: 0.2064
- Validation Accuracy: 0.9196
- 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: {'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 |

|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|

| 0.6893     | 0.5367         | 0.6705          | 0.5536              | 0     |

| 0.6573     | 0.6911         | 0.6171          | 0.8125              | 1     |

| 0.5946     | 0.7876         | 0.5066          | 0.9196              | 2     |

| 0.4681     | 0.9035         | 0.3703          | 0.9107              | 3     |

| 0.3276     | 0.9266         | 0.2682          | 0.9286              | 4     |

| 0.2147     | 0.9614         | 0.2311          | 0.9196              | 5     |

| 0.1356     | 0.9768         | 0.2067          | 0.9286              | 6     |

| 0.0934     | 0.9923         | 0.2064          | 0.9196              | 7     |





### Framework versions



- Transformers 4.44.2

- TensorFlow 2.18.0-dev20240717

- Datasets 2.21.0

- Tokenizers 0.19.1