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# smids_1x_beit_base_adamax_001_fold1

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2333
- Accuracy: 0.8531

## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6722        | 1.0   | 76   | 0.7068          | 0.7346   |
| 0.5257        | 2.0   | 152  | 0.7906          | 0.6978   |
| 0.3766        | 3.0   | 228  | 0.4936          | 0.8030   |
| 0.4703        | 4.0   | 304  | 0.5194          | 0.8047   |
| 0.3758        | 5.0   | 380  | 0.4944          | 0.8047   |
| 0.3685        | 6.0   | 456  | 0.4662          | 0.8364   |
| 0.2812        | 7.0   | 532  | 0.5286          | 0.8314   |
| 0.2831        | 8.0   | 608  | 0.4636          | 0.8331   |
| 0.2359        | 9.0   | 684  | 0.5034          | 0.8063   |
| 0.1426        | 10.0  | 760  | 0.5477          | 0.8280   |
| 0.2668        | 11.0  | 836  | 0.6880          | 0.8130   |
| 0.182         | 12.0  | 912  | 0.6113          | 0.8280   |
| 0.1925        | 13.0  | 988  | 0.5781          | 0.8280   |
| 0.1404        | 14.0  | 1064 | 0.8189          | 0.8114   |
| 0.0795        | 15.0  | 1140 | 0.8425          | 0.8230   |
| 0.0585        | 16.0  | 1216 | 0.6551          | 0.8481   |
| 0.0935        | 17.0  | 1292 | 0.7044          | 0.8347   |
| 0.0369        | 18.0  | 1368 | 0.9110          | 0.8414   |
| 0.0816        | 19.0  | 1444 | 0.9853          | 0.8414   |
| 0.063         | 20.0  | 1520 | 0.7577          | 0.8464   |
| 0.0166        | 21.0  | 1596 | 0.8613          | 0.8381   |
| 0.0172        | 22.0  | 1672 | 0.7211          | 0.8548   |
| 0.0101        | 23.0  | 1748 | 0.9887          | 0.8297   |
| 0.059         | 24.0  | 1824 | 1.1066          | 0.8414   |
| 0.0163        | 25.0  | 1900 | 0.8966          | 0.8481   |
| 0.0425        | 26.0  | 1976 | 0.9615          | 0.8364   |
| 0.0118        | 27.0  | 2052 | 1.0527          | 0.8481   |
| 0.0022        | 28.0  | 2128 | 1.0163          | 0.8464   |
| 0.0009        | 29.0  | 2204 | 1.0736          | 0.8514   |
| 0.0005        | 30.0  | 2280 | 1.0490          | 0.8531   |
| 0.0032        | 31.0  | 2356 | 1.1469          | 0.8514   |
| 0.0106        | 32.0  | 2432 | 1.1588          | 0.8497   |
| 0.06          | 33.0  | 2508 | 1.1292          | 0.8514   |
| 0.0041        | 34.0  | 2584 | 1.0765          | 0.8531   |
| 0.0193        | 35.0  | 2660 | 1.2132          | 0.8548   |
| 0.0004        | 36.0  | 2736 | 1.1489          | 0.8481   |
| 0.0134        | 37.0  | 2812 | 1.2292          | 0.8464   |
| 0.0047        | 38.0  | 2888 | 1.1921          | 0.8514   |
| 0.0036        | 39.0  | 2964 | 1.2034          | 0.8464   |
| 0.0001        | 40.0  | 3040 | 1.1597          | 0.8481   |
| 0.0065        | 41.0  | 3116 | 1.1753          | 0.8548   |
| 0.0001        | 42.0  | 3192 | 1.1808          | 0.8548   |
| 0.0           | 43.0  | 3268 | 1.1898          | 0.8564   |
| 0.0001        | 44.0  | 3344 | 1.2021          | 0.8581   |
| 0.0061        | 45.0  | 3420 | 1.2174          | 0.8564   |
| 0.0           | 46.0  | 3496 | 1.2210          | 0.8548   |
| 0.0025        | 47.0  | 3572 | 1.2289          | 0.8531   |
| 0.0025        | 48.0  | 3648 | 1.2311          | 0.8548   |
| 0.0023        | 49.0  | 3724 | 1.2330          | 0.8531   |
| 0.0044        | 50.0  | 3800 | 1.2333          | 0.8531   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-base-patch16-224", "model-index": [{"name": "smids_1x_beit_base_adamax_001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8530884808013356, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors beit image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/beit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us