---
base_model: dewanshsinghchandel/Bert-Base-Uncased-Pretrained
tags:
- generated_from_keras_callback
model-index:
- name: dewanshsinghchandel/finetune_sst2
  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. -->

# dewanshsinghchandel/finetune_sst2

This model is a fine-tuned version of [dewanshsinghchandel/Bert-Base-Uncased-Pretrained](https://huggingface.co/dewanshsinghchandel/Bert-Base-Uncased-Pretrained) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: nan
- Train Sparse Categorical Accuracy: 0.4220
- Validation Loss: nan
- Validation Sparse Categorical Accuracy: 0.3760
- 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': True, 'is_legacy_optimizer': False, 'learning_rate': 5e-05, '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 |
|:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
| nan        | 0.4160                            | nan             | 0.3760                                 | 0     |
| nan        | 0.4220                            | nan             | 0.3760                                 | 1     |
| nan        | 0.4220                            | nan             | 0.3760                                 | 2     |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.14.0
- Datasets 2.15.0
- Tokenizers 0.15.0