Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
rte_topic_results – AI Model by lengocquangLAB | AlphaNeural AI
You can deploy this model and start earning money today!
lengocquangLAB
/
rte_topic_results
like
0
transformers
safetensors
deberta-v2
text-classification
generated_from_trainer
microsoft/deberta-v3-large
finetune
mit
text-embeddings-inference
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
rte_topic_results
This model is a fine-tuned version of
microsoft/deberta-v3-large
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.0951
Accuracy: 0.7949
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: 6e-06
train_batch_size: 2
eval_batch_size: 2
seed: 42
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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.7823
1.0
1120
1.0633
0.7888
0.5152
2.0
2240
1.0666
0.8048
Framework versions
Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.4.1
Tokenizers 0.22.1
