---
license: apache-2.0
base_model: distilbert-base-uncased-finetuned-sst-2-english
tags:
- generated_from_keras_callback
model-index:
- name: distilbert-base-uncased-finetuned-intel-llm-tf-dataset
  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. -->

# distilbert-base-uncased-finetuned-intel-llm-tf-dataset

This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.5438
- Train Accuracy: 0.7955
- Validation Loss: 1.7204
- Validation Accuracy: 0.4167
- 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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 132, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 1.4394     | 0.6364         | 2.2391          | 0.4167              | 0     |
| 0.7689     | 0.75           | 1.7260          | 0.4167              | 1     |
| 0.5438     | 0.7955         | 1.7204          | 0.4167              | 2     |


### Framework versions

- Transformers 4.34.0
- TensorFlow 2.12.0
- Datasets 2.14.5
- Tokenizers 0.14.0