---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- recall
- precision
- accuracy
- f1
model-index:
- name: UBC-resnet-50-3eph-224
  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. -->

# UBC-resnet-50-3eph-224

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7999
- Recall: 0.6061
- Specificity: 0.8937
- Precision: 0.7089
- Npv: 0.9097
- Accuracy: 0.6860
- F1: 0.6373

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- 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 | Recall | Specificity | Precision | Npv    | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-----------:|:---------:|:------:|:--------:|:------:|
| 0.9759        | 1.0   | 6080  | 0.9368          | 0.5185 | 0.8740      | 0.6852    | 0.8972 | 0.6337   | 0.5423 |
| 0.8617        | 2.0   | 12160 | 0.8285          | 0.5921 | 0.8910      | 0.6964    | 0.9062 | 0.6757   | 0.6221 |
| 0.8362        | 3.0   | 18240 | 0.7999          | 0.6061 | 0.8937      | 0.7089    | 0.9097 | 0.6860   | 0.6373 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3