This is prediction for Suicide and Non-Suicide: Label-1 is Suicide and Label-0 is Non-Suicide.
Transformers_Project
This model is a fine-tuned version of distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1389
- Accuracy: 0.9672
- F1: 0.9672
- Precision: 0.9676
- Recall: 0.9667
- Zero One Loss: 0.0328
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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Zero One Loss |
---|---|---|---|---|---|---|---|---|
0.2495 | 1.0 | 875 | 0.1397 | 0.9552 | 0.9563 | 0.9320 | 0.982 | 0.0448 |
0.0865 | 2.0 | 1750 | 0.1163 | 0.9692 | 0.9692 | 0.9696 | 0.9687 | 0.0308 |
0.0344 | 3.0 | 2625 | 0.1389 | 0.9672 | 0.9672 | 0.9676 | 0.9667 | 0.0328 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
distilbert/distilbert-base-cased