ViditRaj/XLM_Roberta_Hindi_Ads_Classifier

This model is a fine-tuned version of 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