transformers pytorch tensorboard distilbert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
metrics:
- accuracy
- f1
- precision
- recall
tags:
- generated_from_trainer
model-index:
- name: DistilBERT-smaller-BioRED
  results: []
---

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# DistilBERT-smaller-BioRED

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3354
- Accuracy: 0.8900
- F1: 0.5850
- Precision: 0.6149
- Recall: 0.5579

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.3401        | 1.0   | 813  | 0.2766          | 0.8777   | 0.5822 | 0.5487    | 0.6199 |
| 0.2345        | 2.0   | 1626 | 0.3227          | 0.8977   | 0.5358 | 0.7113    | 0.4298 |
| 0.1928        | 3.0   | 2439 | 0.3499          | 0.8946   | 0.5912 | 0.6329    | 0.5546 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
