README.md

---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_keras_callback
model-index:
- name: ukzash1/bert_fineTuned
  results:
  - task:
      type: sequence-classification
    dataset:
      name: glue
      type: cola
    metrics:
    - name: Validation Accuracy
      type: Accuracy
      value: 0.8207
    source:
      name: Hugging Face Model Hub
      url: https://huggingface.co/ukzash1/bert_fineTuned
widget:
- text: I liked this movie
  output:
  - label: Acceptable
    score: 0.8
  - label: Not Acceptable
    score: 0.2
- text: This not is bad
  output:
  - label: Acceptable
    score: 0.2
  - label: Not Acceptable
    score: 0.8
library_name: transformers
language:
- en
metrics:
- accuracy
pipeline_tag: text-classification
---

<!-- 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. -->

# ukzash1/bert_fineTuned

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.3426
- Train Accuracy: 0.8555
- Validation Loss: 0.4083
- Validation Accuracy: 0.8198
- Epoch: 1

## 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': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 0.5409     | 0.7317         | 0.5398          | 0.7756              | 0     |
| 0.3426     | 0.8555         | 0.4083          | 0.8198              | 1     |


### Framework versions

- Transformers 4.38.2
- TensorFlow 2.13.0
- Datasets 2.20.0
- Tokenizers 0.15.2