---
license: apache-2.0
base_model: microsoft/resnet-101
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [microsoft/resnet-101](https://huggingface.co/microsoft/resnet-101) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1744
- Accuracy: 0.9428
- F1: 0.9428
- Precision: 0.9428
- Recall: 0.9428

## 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: 0.01
- train_batch_size: 128
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 16
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.2883        | 1.0   | 99   | 0.3757          | 0.8563   | 0.8563 | 0.8563    | 0.8563 |
| 0.2195        | 2.0   | 198  | 0.2293          | 0.9178   | 0.9178 | 0.9178    | 0.9178 |
| 0.1936        | 3.0   | 297  | 0.2120          | 0.9149   | 0.9149 | 0.9149    | 0.9149 |
| 0.163         | 4.0   | 396  | 0.1744          | 0.9428   | 0.9428 | 0.9428    | 0.9428 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1