metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: birds_transform_full
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.7303427419354839
birds_transform_full
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Accuracy: 0.7303
- Loss: 1.4588
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 5.6427 | 1.0 | 1984 | 0.4519 | 5.2504 |
| 4.6563 | 2.0 | 3968 | 0.5068 | 4.2749 |
| 3.6656 | 3.0 | 5952 | 0.5454 | 3.3311 |
| 2.7653 | 4.0 | 7936 | 0.5748 | 2.5181 |
| 2.0465 | 5.0 | 9920 | 0.6300 | 1.9205 |
| 1.5876 | 6.0 | 11904 | 0.6593 | 1.5696 |
| 1.3174 | 7.0 | 13888 | 0.6870 | 1.3831 |
| 1.1279 | 8.0 | 15872 | 0.7064 | 1.2516 |
| 1.0051 | 9.0 | 17856 | 0.7067 | 1.1999 |
| 0.9318 | 10.0 | 19840 | 0.7077 | 1.1631 |
| 0.8294 | 11.0 | 21824 | 0.7089 | 1.1444 |
| 0.7976 | 12.0 | 23808 | 0.7175 | 1.1156 |
| 0.7084 | 13.0 | 25792 | 0.7218 | 1.1209 |
| 0.6752 | 14.0 | 27776 | 0.7198 | 1.1032 |
| 0.6641 | 15.0 | 29760 | 0.7198 | 1.1192 |
| 0.6083 | 16.0 | 31744 | 0.7268 | 1.1044 |
| 0.5703 | 17.0 | 33728 | 0.7248 | 1.1287 |
| 0.5376 | 18.0 | 35712 | 0.7286 | 1.1115 |
| 0.5073 | 19.0 | 37696 | 0.7218 | 1.1429 |
| 0.5072 | 20.0 | 39680 | 0.7208 | 1.1519 |
| 0.4945 | 21.0 | 41664 | 0.7228 | 1.1636 |
| 0.4651 | 22.0 | 43648 | 0.7213 | 1.1771 |
| 0.4408 | 23.0 | 45632 | 0.7233 | 1.1650 |
| 0.4222 | 24.0 | 47616 | 0.7157 | 1.1841 |
| 0.409 | 25.0 | 49600 | 0.7145 | 1.2150 |
| 0.403 | 26.0 | 51584 | 0.7152 | 1.2203 |
| 0.3813 | 27.0 | 53568 | 0.7238 | 1.2064 |
| 0.3756 | 28.0 | 55552 | 0.7177 | 1.2526 |
| 0.365 | 29.0 | 57536 | 0.7208 | 1.2670 |
| 0.3729 | 30.0 | 59520 | 0.7180 | 1.2659 |
| 0.36 | 31.0 | 61504 | 0.7127 | 1.2545 |
| 0.3596 | 32.0 | 63488 | 0.7182 | 1.2728 |
| 0.3606 | 33.0 | 65472 | 0.7180 | 1.2886 |
| 0.325 | 34.0 | 67456 | 0.7157 | 1.2929 |
| 0.329 | 35.0 | 69440 | 0.7205 | 1.3074 |
| 0.3431 | 36.0 | 71424 | 0.7185 | 1.3122 |
| 0.3206 | 37.0 | 73408 | 0.7233 | 1.2993 |
| 0.3137 | 38.0 | 75392 | 0.7220 | 1.3206 |
| 0.3265 | 39.0 | 77376 | 0.7180 | 1.3246 |
| 0.3332 | 40.0 | 79360 | 0.7240 | 1.3163 |
| 0.3193 | 41.0 | 81344 | 0.7288 | 1.3259 |
| 0.3242 | 42.0 | 83328 | 0.7215 | 1.3320 |
| 0.2976 | 43.0 | 85312 | 0.7213 | 1.3283 |
| 0.3191 | 44.0 | 87296 | 0.7195 | 1.3453 |
| 0.3067 | 45.0 | 89280 | 0.7243 | 1.3550 |
| 0.2994 | 46.0 | 91264 | 0.7240 | 1.3324 |
| 0.3072 | 47.0 | 93248 | 0.7263 | 1.3412 |
| 0.2932 | 48.0 | 95232 | 0.7245 | 1.3345 |
| 0.2919 | 49.0 | 97216 | 0.7266 | 1.3759 |
| 0.2922 | 50.0 | 99200 | 0.7225 | 1.3873 |
| 0.304 | 51.0 | 101184 | 0.7235 | 1.3631 |
| 0.2898 | 52.0 | 103168 | 0.7205 | 1.3819 |
| 0.2773 | 53.0 | 105152 | 0.7251 | 1.3827 |
| 0.2756 | 54.0 | 107136 | 0.7228 | 1.3770 |
| 0.2789 | 55.0 | 109120 | 0.7248 | 1.3822 |
| 0.261 | 56.0 | 111104 | 0.7263 | 1.3878 |
| 0.2593 | 57.0 | 113088 | 0.7240 | 1.3955 |
| 0.2801 | 58.0 | 115072 | 0.7256 | 1.3659 |
| 0.2632 | 59.0 | 117056 | 0.7301 | 1.3719 |
| 0.2811 | 60.0 | 119040 | 0.7321 | 1.3775 |
| 0.2267 | 61.0 | 121024 | 0.7256 | 1.3689 |
| 0.2676 | 62.0 | 123008 | 0.7245 | 1.4069 |
| 0.2523 | 63.0 | 124992 | 0.7230 | 1.4166 |
| 0.2622 | 64.0 | 126976 | 0.7296 | 1.4018 |
| 0.2467 | 65.0 | 128960 | 0.7256 | 1.4287 |
| 0.2504 | 66.0 | 130944 | 0.7314 | 1.4019 |
| 0.2468 | 67.0 | 132928 | 0.7303 | 1.4058 |
| 0.2098 | 68.0 | 134912 | 0.7308 | 1.4093 |
| 0.2382 | 69.0 | 136896 | 0.7293 | 1.4206 |
| 0.2304 | 70.0 | 138880 | 0.7301 | 1.4078 |
| 0.251 | 71.0 | 140864 | 0.7251 | 1.4275 |
| 0.237 | 72.0 | 142848 | 0.7288 | 1.4283 |
| 0.2485 | 73.0 | 144832 | 0.7281 | 1.4338 |
| 0.2229 | 74.0 | 146816 | 0.7253 | 1.4386 |
| 0.2472 | 75.0 | 148800 | 0.7210 | 1.4440 |
| 0.2149 | 76.0 | 150784 | 0.7230 | 1.4319 |
| 0.2337 | 77.0 | 152768 | 0.7261 | 1.4422 |
| 0.2063 | 78.0 | 154752 | 0.7268 | 1.4456 |
| 0.216 | 79.0 | 156736 | 0.7218 | 1.4426 |
| 0.2249 | 80.0 | 158720 | 0.7198 | 1.4533 |
| 0.2148 | 81.0 | 160704 | 0.7230 | 1.4480 |
| 0.2321 | 82.0 | 162688 | 0.7273 | 1.4416 |
| 0.2306 | 83.0 | 164672 | 0.7286 | 1.4392 |
| 0.213 | 84.0 | 166656 | 0.7263 | 1.4609 |
| 0.2202 | 85.0 | 168640 | 0.7266 | 1.4590 |
| 0.206 | 86.0 | 170624 | 0.7245 | 1.4638 |
| 0.1987 | 87.0 | 172608 | 0.7251 | 1.4626 |
| 0.2181 | 88.0 | 174592 | 0.7261 | 1.4615 |
| 0.2076 | 89.0 | 176576 | 0.7253 | 1.4665 |
| 0.1999 | 90.0 | 178560 | 0.7251 | 1.4569 |
| 0.2287 | 91.0 | 180544 | 0.7266 | 1.4591 |
| 0.1985 | 92.0 | 182528 | 0.7263 | 1.4508 |
| 0.2166 | 93.0 | 184512 | 0.7266 | 1.4621 |
| 0.1943 | 94.0 | 186496 | 0.7276 | 1.4649 |
| 0.2189 | 95.0 | 188480 | 0.7293 | 1.4555 |
| 0.1911 | 96.0 | 190464 | 0.7306 | 1.4565 |
| 0.1954 | 97.0 | 192448 | 0.7271 | 1.4624 |
| 0.2053 | 98.0 | 194432 | 0.7286 | 1.4603 |
| 0.2067 | 99.0 | 196416 | 0.7306 | 1.4589 |
| 0.1917 | 100.0 | 198400 | 0.7303 | 1.4588 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1