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---
license: apache-2.0
base_model: facebook/convnextv2-nano-22k-384
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
- matthews_correlation
model-index:
- name: convnextv2-nano-22k-384-boulderspot-vN
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. -->
# convnextv2-nano-22k-384-boulderspot-vN
This model is a fine-tuned version of [facebook/convnextv2-nano-22k-384](https://huggingface.co/facebook/convnextv2-nano-22k-384) on the pszemraj/boulderspot dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0340
- Accuracy: 0.9883
- F1: 0.9883
- Precision: 0.9883
- Recall: 0.9883
- Matthews Correlation: 0.8962
## 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: 7890
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 5.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:--------------------:|
| 0.1102 | 1.0 | 203 | 0.0431 | 0.9839 | 0.9840 | 0.9841 | 0.9839 | 0.8590 |
| 0.0559 | 2.0 | 406 | 0.0476 | 0.9839 | 0.9845 | 0.9858 | 0.9839 | 0.8709 |
| 0.0402 | 3.0 | 609 | 0.0464 | 0.9810 | 0.9817 | 0.9831 | 0.9810 | 0.8468 |
| 0.0334 | 4.0 | 813 | 0.0348 | 0.9868 | 0.9869 | 0.9870 | 0.9868 | 0.8846 |
| 0.0445 | 4.99 | 1015 | 0.0340 | 0.9883 | 0.9883 | 0.9883 | 0.9883 | 0.8962 |
### Framework versions
- Transformers 4.39.2
- Pytorch 2.4.0.dev20240328+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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