---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: cakiki/distilbert-base-uncased-finetuned-tweet-sentiment
  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. -->

# cakiki/distilbert-base-uncased-finetuned-tweet-sentiment

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: 0.1025
- Train Sparse Categorical Accuracy: 0.9511
- Validation Loss: 0.1455
- Validation Sparse Categorical Accuracy: 0.9365
- 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', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
|:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
| 0.5409     | 0.8158                            | 0.2115          | 0.9265                                 | 0     |
| 0.1442     | 0.9373                            | 0.1411          | 0.9380                                 | 1     |
| 0.1025     | 0.9511                            | 0.1455          | 0.9365                                 | 2     |


### Framework versions

- Transformers 4.18.0
- TensorFlow 2.9.0-rc0
- Datasets 2.1.0
- Tokenizers 0.12.1