metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
base_model: distilbert-base-uncased
model-index:
- name: distilbert-base-uncased_finetuned_text_2_disease_cel
results: []
distilbert-base-uncased_finetuned_text_2_disease_cel
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: 0.2732
- Accuracy: 0.9865
- F1: 0.9864
- Recall: 0.9865
- Precision: 0.9879
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
|---|---|---|---|---|---|---|---|
| 1.3868 | 1.0 | 167 | 1.1692 | 0.8649 | 0.8458 | 0.8649 | 0.8573 |
| 0.5345 | 2.0 | 334 | 0.4214 | 0.9745 | 0.9736 | 0.9745 | 0.9769 |
| 0.3472 | 3.0 | 501 | 0.2732 | 0.9865 | 0.9864 | 0.9865 | 0.9879 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2