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hinglish-toxicity-roberta – AI Model by darelphilip | AlphaNeural AI
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darelphilip
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hinglish-toxicity-roberta
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transformers
safetensors
xlm-roberta
text-classification
generated_from_trainer
l3cube-pune/hing-roberta
finetune
cc-by-4.0
text-embeddings-inference
endpoints_compatible
us
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hinglish-toxicity-roberta
This model is a fine-tuned version of
l3cube-pune/hing-roberta
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.7698
Macro F1: 0.5388
Micro F1: 0.6376
Precision: 0.4402
Recall: 0.7391
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:
learning_rate: 3e-05
train_batch_size: 8
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Macro F1
Micro F1
Precision
Recall
1.5812
1.0
6531
0.9446
0.5566
0.6546
0.5257
0.6218
1.4899
2.0
13062
0.7698
0.5388
0.6376
0.4402
0.7391
Framework versions
Transformers 5.15.0
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
