pytorch convnext image-classification transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: flyswot_iiif
  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. -->

# flyswot_iiif

This model is a fine-tuned version of [facebook/convnext-base-224-22k](https://huggingface.co/facebook/convnext-base-224-22k) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 6.1280
- F1: 0.0034

## 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: 64
- eval_batch_size: 64
- seed: 666
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 8.5184        | 0.26  | 500   | 7.9280          | 0.0005 |
| 7.7409        | 0.52  | 1000  | 7.5824          | 0.0007 |
| 7.4649        | 0.78  | 1500  | 7.3841          | 0.0010 |
| 7.3285        | 1.04  | 2000  | 7.2652          | 0.0012 |
| 7.1404        | 1.3   | 2500  | 7.1559          | 0.0014 |
| 7.0322        | 1.56  | 3000  | 7.0551          | 0.0016 |
| 6.9197        | 1.82  | 3500  | 6.9449          | 0.0019 |
| 6.7822        | 2.09  | 4000  | 6.8773          | 0.0018 |
| 6.6506        | 2.35  | 4500  | 6.7980          | 0.0020 |
| 6.5811        | 2.61  | 5000  | 6.7382          | 0.0022 |
| 6.538         | 2.87  | 5500  | 6.6582          | 0.0022 |
| 6.4136        | 3.13  | 6000  | 6.6013          | 0.0024 |
| 6.3325        | 3.39  | 6500  | 6.5369          | 0.0024 |
| 6.2566        | 3.65  | 7000  | 6.4875          | 0.0025 |
| 6.2285        | 3.91  | 7500  | 6.4342          | 0.0027 |
| 6.1281        | 4.17  | 8000  | 6.4066          | 0.0027 |
| 6.0762        | 4.43  | 8500  | 6.3674          | 0.0027 |
| 6.0309        | 4.69  | 9000  | 6.3336          | 0.0027 |
| 6.0123        | 4.95  | 9500  | 6.2932          | 0.0030 |
| 5.9089        | 5.21  | 10000 | 6.2835          | 0.0029 |
| 5.8901        | 5.47  | 10500 | 6.2481          | 0.0030 |
| 5.86          | 5.74  | 11000 | 6.2295          | 0.0030 |
| 5.8586        | 6.0   | 11500 | 6.2068          | 0.0033 |
| 5.7768        | 6.26  | 12000 | 6.1937          | 0.0031 |
| 5.7591        | 6.52  | 12500 | 6.1916          | 0.0032 |
| 5.7443        | 6.78  | 13000 | 6.1579          | 0.0033 |
| 5.7125        | 7.04  | 13500 | 6.1478          | 0.0033 |
| 5.6751        | 7.3   | 14000 | 6.1379          | 0.0035 |
| 5.6648        | 7.56  | 14500 | 6.1304          | 0.0035 |
| 5.6644        | 7.82  | 15000 | 6.1280          | 0.0034 |


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.6
