File size: 2,100 Bytes
f3b8261 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 |
---
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_class
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-tiny-1k-224-finetuned-hand_class
This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5260
- Accuracy: 0.7739
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.663 | 1.0 | 14 | 0.5878 | 0.6809 |
| 0.5594 | 2.0 | 28 | 0.5597 | 0.7337 |
| 0.5364 | 3.0 | 42 | 0.5466 | 0.7412 |
| 0.545 | 4.0 | 56 | 0.5489 | 0.7462 |
| 0.5267 | 5.0 | 70 | 0.5484 | 0.7462 |
| 0.506 | 6.0 | 84 | 0.5320 | 0.7663 |
| 0.5196 | 7.0 | 98 | 0.5328 | 0.7638 |
| 0.4933 | 8.0 | 112 | 0.5293 | 0.7663 |
| 0.4809 | 9.0 | 126 | 0.5280 | 0.7739 |
| 0.4836 | 10.0 | 140 | 0.5260 | 0.7739 |
### Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
|