metadata
library_name: transformers
base_model: Gaborandi/Medicaldistilbert
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Medicaldistilbert_finetuned
results: []
Medicaldistilbert_finetuned
This model is a fine-tuned version of Gaborandi/Medicaldistilbert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2582
- Precision: 0.5383
- Recall: 0.6047
- F1: 0.5696
- Accuracy: 0.9166
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 125 | 0.3249 | 0.4618 | 0.4849 | 0.4731 | 0.9000 |
| No log | 2.0 | 250 | 0.2673 | 0.5274 | 0.5930 | 0.5583 | 0.9151 |
| No log | 3.0 | 375 | 0.2582 | 0.5383 | 0.6047 | 0.5696 | 0.9166 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0