---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: LovenOO/distilBERT_without_preprocessing
  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. -->

# LovenOO/distilBERT_without_preprocessing

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: 0.1466
- Validation Loss: 0.3625
- Train Precision: 0.8491
- Train Recall: 0.8642
- Train F1: 0.8544
- Train Accuracy: 0.8906
- Epoch: 5

## 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', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2565, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
| 0.8177     | 0.4723          | 0.8407          | 0.7879       | 0.7948   | 0.8575         | 0     |
| 0.3642     | 0.3777          | 0.8666          | 0.8315       | 0.8465   | 0.8847         | 1     |
| 0.2734     | 0.3804          | 0.8466          | 0.8563       | 0.8471   | 0.8872         | 2     |
| 0.2020     | 0.3704          | 0.8526          | 0.8663       | 0.8551   | 0.8896         | 3     |
| 0.1638     | 0.3625          | 0.8491          | 0.8642       | 0.8544   | 0.8906         | 4     |
| 0.1466     | 0.3625          | 0.8491          | 0.8642       | 0.8544   | 0.8906         | 5     |


### Framework versions

- Transformers 4.24.0
- TensorFlow 2.13.0
- Datasets 2.14.2
- Tokenizers 0.11.0