metadata
license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: convnextv2-tiny-1k-224-finetuned-hand-final
results: []
convnextv2-tiny-1k-224-finetuned-hand-final
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: 0.6638
- Accuracy: 0.7563
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.6669 | 1.0 | 14 | 0.6050 | 0.6834 |
0.5796 | 2.0 | 28 | 0.5599 | 0.7362 |
0.5417 | 3.0 | 42 | 0.5486 | 0.7437 |
0.5466 | 4.0 | 56 | 0.5528 | 0.7387 |
0.5213 | 5.0 | 70 | 0.5673 | 0.7462 |
0.493 | 6.0 | 84 | 0.5432 | 0.7613 |
0.5051 | 7.0 | 98 | 0.5457 | 0.7513 |
0.4656 | 8.0 | 112 | 0.5444 | 0.7563 |
0.4399 | 9.0 | 126 | 0.5430 | 0.7613 |
0.4213 | 10.0 | 140 | 0.5507 | 0.7613 |
0.4118 | 11.0 | 154 | 0.5619 | 0.7538 |
0.4015 | 12.0 | 168 | 0.5383 | 0.7513 |
0.3785 | 13.0 | 182 | 0.5567 | 0.7563 |
0.3487 | 14.0 | 196 | 0.5972 | 0.7462 |
0.3401 | 15.0 | 210 | 0.6059 | 0.7462 |
0.3215 | 16.0 | 224 | 0.6051 | 0.7563 |
0.3171 | 17.0 | 238 | 0.6228 | 0.7513 |
0.2971 | 18.0 | 252 | 0.6529 | 0.7563 |
0.3111 | 19.0 | 266 | 0.6309 | 0.7588 |
0.2722 | 20.0 | 280 | 0.6444 | 0.7588 |
0.2677 | 21.0 | 294 | 0.6373 | 0.7588 |
0.2721 | 22.0 | 308 | 0.6393 | 0.7538 |
0.2694 | 23.0 | 322 | 0.6382 | 0.7613 |
0.2731 | 24.0 | 336 | 0.6543 | 0.7613 |
0.257 | 25.0 | 350 | 0.6638 | 0.7563 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3