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intent-recog – AI Model by Ratansingh648 | AlphaNeural AI
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Ratansingh648
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intent-recog
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transformers
pytorch
xlm-roberta
generated_from_trainer
FacebookAI/xlm-roberta-base
finetune
mit
endpoints_compatible
us
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intent-recog
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: 0.0174
F1: 0.9934
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: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
F1
0.0351
1.0
10523
0.0174
0.9934
Framework versions
Transformers 4.33.2
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3
