bert-large-uncased-detect-depression-stage-one
This model is a fine-tuned version of bert-large-uncased on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.7875
- eval_accuracy: 0.752
- eval_f1: 0.8092
- eval_runtime: 112.7187
- eval_samples_per_second: 8.872
- eval_steps_per_second: 2.218
- epoch: 3.0
- step: 4506
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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3