README.md

metadata

library_name: transformers
license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: 2025-02-10-08-48-20-convnextv2-tiny-1k-224
    results: []

2025-02-10-08-48-20-convnextv2-tiny-1k-224

This model is a fine-tuned version of facebook/convnextv2-tiny-1k-224 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0276
• Precision: 0.9953
• Recall: 0.9951
• F1: 0.9951
• Accuracy: 0.9952
• Top1 Accuracy: 0.9951
• Error Rate: 0.0048

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: 0.0002
• train_batch_size: 32
• eval_batch_size: 32
• seed: 3407
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy	Top1 Accuracy	Error Rate
1.1857	1.0	103	0.2269	0.9480	0.9390	0.9396	0.9449	0.9390	0.0551
0.2112	2.0	206	0.1580	0.9583	0.9561	0.9563	0.9554	0.9561	0.0446
0.1067	3.0	309	0.1165	0.9634	0.9610	0.9613	0.9571	0.9610	0.0429
0.0922	4.0	412	0.1750	0.9608	0.9537	0.9532	0.9549	0.9537	0.0451
0.0346	5.0	515	0.0920	0.9827	0.9805	0.9805	0.9845	0.9805	0.0155
0.018	6.0	618	0.0483	0.9881	0.9878	0.9877	0.9886	0.9878	0.0114
0.0114	7.0	721	0.0276	0.9953	0.9951	0.9951	0.9952	0.9951	0.0048
0.0067	8.0	824	0.0423	0.9906	0.9902	0.9903	0.9894	0.9902	0.0106
0.0014	9.0	927	0.0310	0.9953	0.9951	0.9951	0.9952	0.9951	0.0048

Framework versions

• Transformers 4.45.2
• Pytorch 2.5.1+cu124
• Datasets 3.2.0
• Tokenizers 0.20.3