roberta_base_classification_model_depression_detection

This model is a fine-tuned version of FacebookAI/roberta-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0822
• Accuracy: 0.9819
• F1 Score: 0.9828

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: 3e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 50
• num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Score
No log	1.0	386	0.0517	0.9767	0.9776
0.1806	2.0	773	0.0383	0.9871	0.9878
0.0668	3.0	1159	0.0614	0.9845	0.9851
0.0294	3.99	1544	0.0822	0.9819	0.9828

Framework versions

• Transformers 4.39.3
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.15.2