---
license: mit
tags:
- generated_from_keras_callback
model-index:
- name: ViditRaj/XLM_Roberta_Hindi_Ads_Classifier
  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. -->

# ViditRaj/XLM_Roberta_Hindi_Ads_Classifier

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.3258
- Validation Loss: 0.2867
- Train Accuracy: 0.9149
- Epoch: 4

## 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': 2e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.3738     | 0.2117          | 0.9301         | 0     |
| 0.2323     | 0.1927          | 0.9347         | 1     |
| 0.2013     | 0.1739          | 0.9377         | 2     |
| 0.4551     | 0.5800          | 0.7219         | 3     |
| 0.3258     | 0.2867          | 0.9149         | 4     |


### Framework versions

- Transformers 4.27.3
- TensorFlow 2.11.0
- Datasets 2.10.1
- Tokenizers 0.13.2