---
license: apache-2.0
base_model: facebook/convnext-base-384-22k-1k
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: convnext-base-384-22k-1k-Kontur-competition-1.3K
  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. -->

# convnext-base-384-22k-1k-Kontur-competition-1.3K

This model is a fine-tuned version of [facebook/convnext-base-384-22k-1k](https://huggingface.co/facebook/convnext-base-384-22k-1k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0003

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 0.95  | 9    | 0.5273          |
| 0.6611        | 2.0   | 19   | 0.1518          |
| 0.2686        | 2.95  | 28   | 0.0266          |
| 0.0899        | 4.0   | 38   | 0.0066          |
| 0.0379        | 4.95  | 47   | 0.0025          |
| 0.0202        | 6.0   | 57   | 0.0020          |
| 0.0048        | 6.95  | 66   | 0.0010          |
| 0.0056        | 8.0   | 76   | 0.0011          |
| 0.0011        | 8.95  | 85   | 0.0005          |
| 0.0017        | 10.0  | 95   | 0.0014          |
| 0.0076        | 10.95 | 104  | 0.0004          |
| 0.0018        | 12.0  | 114  | 0.0003          |
| 0.0027        | 12.95 | 123  | 0.0003          |
| 0.0008        | 14.0  | 133  | 0.0003          |
| 0.0008        | 14.21 | 135  | 0.0003          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2