---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilBERT_bio_pv_superset
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# distilBERT_bio_pv_superset

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: 0.2328
- Precision: 0.5462
- Recall: 0.5325
- F1: 0.5393
- Accuracy: 0.9495

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0964        | 1.0   | 5467  | 0.1593          | 0.4625    | 0.3682 | 0.4100 | 0.9416   |
| 0.1918        | 2.0   | 10934 | 0.1541          | 0.4796    | 0.4658 | 0.4726 | 0.9436   |
| 0.0394        | 3.0   | 16401 | 0.1508          | 0.5349    | 0.4744 | 0.5028 | 0.9482   |
| 0.1207        | 4.0   | 21868 | 0.1615          | 0.5422    | 0.4953 | 0.5177 | 0.9490   |
| 0.0221        | 5.0   | 27335 | 0.1827          | 0.5377    | 0.5018 | 0.5191 | 0.9487   |
| 0.0629        | 6.0   | 32802 | 0.1874          | 0.5479    | 0.5130 | 0.5299 | 0.9493   |
| 0.0173        | 7.0   | 38269 | 0.2025          | 0.5388    | 0.5323 | 0.5356 | 0.9488   |
| 0.2603        | 8.0   | 43736 | 0.2148          | 0.5437    | 0.5397 | 0.5417 | 0.9493   |
| 0.0378        | 9.0   | 49203 | 0.2323          | 0.5430    | 0.5194 | 0.5310 | 0.9489   |
| 0.031         | 10.0  | 54670 | 0.2328          | 0.5462    | 0.5325 | 0.5393 | 0.9495   |


### Framework versions

- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1