---
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_v1
  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_v1

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: 0.0574
- Accuracy: 0.9985
- F1: 0.9985
- Recall: 0.9985
- Precision: 0.9986

## 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: 3e-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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.8645        | 1.0   | 167  | 0.6333          | 0.9354   | 0.9288 | 0.9354 | 0.9501    |
| 0.1886        | 2.0   | 334  | 0.1070          | 0.9970   | 0.9970 | 0.9970 | 0.9971    |
| 0.0902        | 3.0   | 501  | 0.0574          | 0.9985   | 0.9985 | 0.9985 | 0.9986    |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2