---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-uncased_finetuned_text_2_disease_cel

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co./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