---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: DearSola/my-awesome-model_1113
  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. -->

# DearSola/my-awesome-model_1113

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.1382
- Validation Loss: 0.3086
- Train Accuracy: 0.8771
- Train F1: 0.7370
- Train Precision: 0.7584
- Train Recall: 0.7168
- Epoch: 2

## 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 675, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Train F1 | Train Precision | Train Recall | Epoch |
|:----------:|:---------------:|:--------------:|:--------:|:---------------:|:------------:|:-----:|
| 0.4029     | 0.3051          | 0.8618         | 0.6846   | 0.7579          | 0.6243       | 0     |
| 0.2311     | 0.2948          | 0.8701         | 0.7497   | 0.6983          | 0.8092       | 1     |
| 0.1382     | 0.3086          | 0.8771         | 0.7370   | 0.7584          | 0.7168       | 2     |


### Framework versions

- Transformers 4.41.1
- TensorFlow 2.17.0
- Datasets 2.20.0
- Tokenizers 0.19.1