---
license: apache-2.0
base_model: bert-large-uncased
tags:
- generated_from_keras_callback
model-index:
- name: vedantjumle/bert-2
  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. -->

# vedantjumle/bert-2

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0761
- Validation Loss: 0.4911
- Train Accuracy: 0.8833
- Epoch: 20

## 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 6000, '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 | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 4.9762     | 4.7210          | 0.0767         | 0     |
| 4.4240     | 4.0959          | 0.4233         | 1     |
| 3.6373     | 3.4046          | 0.69           | 2     |
| 2.8675     | 2.7514          | 0.8233         | 3     |
| 2.1664     | 2.1956          | 0.8667         | 4     |
| 1.5991     | 1.7330          | 0.86           | 5     |
| 1.1413     | 1.4153          | 0.8833         | 6     |
| 0.8233     | 1.1592          | 0.8867         | 7     |
| 0.6009     | 0.9746          | 0.9033         | 8     |
| 0.4423     | 0.8468          | 0.9067         | 9     |
| 0.3338     | 0.7524          | 0.8967         | 10    |
| 0.2628     | 0.6865          | 0.8967         | 11    |
| 0.2142     | 0.6403          | 0.8933         | 12    |
| 0.1774     | 0.6060          | 0.8933         | 13    |
| 0.1522     | 0.5770          | 0.89           | 14    |
| 0.1316     | 0.5526          | 0.89           | 15    |
| 0.1163     | 0.5336          | 0.8867         | 16    |
| 0.1027     | 0.5190          | 0.89           | 17    |
| 0.0923     | 0.5043          | 0.8933         | 18    |
| 0.0851     | 0.4970          | 0.8867         | 19    |
| 0.0761     | 0.4911          | 0.8833         | 20    |


### Framework versions

- Transformers 4.34.0
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.14.1