File size: 2,519 Bytes
e890f1d | 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 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 | ---
library_name: transformers
license: apache-2.0
base_model: WinKawaks/vit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: gender_mozilla_mel_spec_Vit_vit-tiny-patch16-224_2
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9366666666666666
---
<!-- 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. -->
# gender_mozilla_mel_spec_Vit_vit-tiny-patch16-224_2
This model is a fine-tuned version of [WinKawaks/vit-tiny-patch16-224](https://huggingface.co/WinKawaks/vit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3420
- Accuracy: 0.9367
## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6724 | 1.0 | 11 | 0.3985 | 0.87 |
| 0.3071 | 2.0 | 22 | 0.2514 | 0.92 |
| 0.1861 | 3.0 | 33 | 0.2074 | 0.93 |
| 0.1192 | 4.0 | 44 | 0.2194 | 0.94 |
| 0.0655 | 5.0 | 55 | 0.2362 | 0.9367 |
| 0.0268 | 6.0 | 66 | 0.2645 | 0.9333 |
| 0.0239 | 7.0 | 77 | 0.3006 | 0.9333 |
| 0.0049 | 8.0 | 88 | 0.3445 | 0.9333 |
| 0.007 | 9.0 | 99 | 0.3609 | 0.93 |
| 0.0005 | 10.0 | 110 | 0.3420 | 0.9367 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0
|