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Depressive-detector – AI Model by JimminDev | AlphaNeural AI
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JimminDev
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Depressive-detector
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transformers
tensorboard
safetensors
deberta-v2
text-classification
generated_from_trainer
MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7
finetune
mit
autotrain_compatible
endpoints_compatible
us
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Depressive-detector
This model is a fine-tuned version of
MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7
on the None dataset.
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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 4
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
Accuracy
No log
1.0
80
0.6949
0.625
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1
