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roberta-base-detect-depression-large-dataset – AI Model by hoanghoavienvo | AlphaNeural AI
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hoanghoavienvo
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roberta-base-detect-depression-large-dataset
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transformers
pytorch
tensorboard
roberta
text-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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roberta-base-detect-depression-large-dataset
This model is a fine-tuned version of
roberta-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.5713
Accuracy: 0.785
F1: 0.8432
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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.6291
1.0
1157
0.6365
0.675
0.7860
0.6281
2.0
2314
0.6803
0.602
0.7509
0.6344
3.0
3471
0.6679
0.612
0.7557
0.6367
4.0
4628
0.6746
0.6
0.7500
0.6193
5.0
5785
0.5713
0.785
0.8432
Framework versions
Transformers 4.30.1
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3
