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---
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
|