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Q9-PHQ

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metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: Q9-PHQ
    results: []

Q9-PHQ

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

  • Loss: 0.3267
  • Accuracy: 0.8875
  • Mcc: 0.6295

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: 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: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy Mcc
No log 1.0 51 0.4744 0.8075 0.0
No log 2.0 102 0.3437 0.8825 0.5807
No log 3.0 153 0.3191 0.8825 0.6130
No log 4.0 204 0.3412 0.8725 0.6176
No log 5.0 255 0.3267 0.8875 0.6295

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1