metadata
license: mit
base_model: austin/Austin-MeDeBERTa
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: fold_0
results: []
fold_0
This model is a fine-tuned version of austin/Austin-MeDeBERTa on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0098
- Precision: 0.7014
- Recall: 0.6918
- F1: 0.6966
- Accuracy: 0.9975
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: 5
- eval_batch_size: 5
- 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0445 | 1.0 | 708 | 0.0106 | 0.6792 | 0.4932 | 0.5714 | 0.9971 |
| 0.0098 | 2.0 | 1416 | 0.0095 | 0.6875 | 0.6781 | 0.6828 | 0.9974 |
| 0.0035 | 3.0 | 2124 | 0.0098 | 0.7014 | 0.6918 | 0.6966 | 0.9975 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2