Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
xlm-roberta-base-finetuned-formality-mcls – AI Model by ViHr | AlphaNeural AI
You can deploy this model and start earning money today!
ViHr
/
xlm-roberta-base-finetuned-formality-mcls
like
0
transformers
safetensors
xlm-roberta
text-classification
generated_from_trainer
FacebookAI/xlm-roberta-base
finetune
mit
text-embeddings-inference
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
xlm-roberta-base-finetuned-formality-mcls
This model is a fine-tuned version of
xlm-roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3549
Accuracy: 0.8264
F1: 0.8264
Precision: 0.8445
Recall: 0.8264
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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 64
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
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
2.8712
1.0
3241
0.3501
0.8251
0.8250
0.8441
0.8251
2.6744
2.0
6482
0.3414
0.8320
0.8321
0.8468
0.8320
2.4269
3.0
9723
0.3549
0.8264
0.8264
0.8445
0.8264
Framework versions
Transformers 5.8.1
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
