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_v2
results: []
distilbert-base-uncased_finetuned_text_2_disease_cel_v2
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: 0.0252
- Accuracy: 1.0
- F1: 1.0
- Recall: 1.0
- Precision: 1.0
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: 4e-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 |
|---|---|---|---|---|---|---|---|
| 0.5425 | 1.0 | 167 | 0.3685 | 0.9640 | 0.9631 | 0.9640 | 0.9698 |
| 0.0887 | 2.0 | 334 | 0.0424 | 0.9985 | 0.9985 | 0.9985 | 0.9986 |
| 0.0399 | 3.0 | 501 | 0.0261 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2