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# SMIDS_1x_beit_large_SGD_lr00001_fold2

This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2040
- Accuracy: 0.3478

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7982        | 1.0   | 150  | 1.6666          | 0.2912   |
| 1.6479        | 2.0   | 300  | 1.6408          | 0.2862   |
| 1.7064        | 3.0   | 450  | 1.6163          | 0.2862   |
| 1.6283        | 4.0   | 600  | 1.5928          | 0.2845   |
| 1.6092        | 5.0   | 750  | 1.5702          | 0.2829   |
| 1.5889        | 6.0   | 900  | 1.5488          | 0.2829   |
| 1.6576        | 7.0   | 1050 | 1.5283          | 0.2829   |
| 1.5717        | 8.0   | 1200 | 1.5088          | 0.2812   |
| 1.5492        | 9.0   | 1350 | 1.4901          | 0.2812   |
| 1.4083        | 10.0  | 1500 | 1.4722          | 0.2829   |
| 1.489         | 11.0  | 1650 | 1.4552          | 0.2812   |
| 1.4997        | 12.0  | 1800 | 1.4391          | 0.2829   |
| 1.4083        | 13.0  | 1950 | 1.4235          | 0.2845   |
| 1.4643        | 14.0  | 2100 | 1.4089          | 0.2879   |
| 1.2956        | 15.0  | 2250 | 1.3949          | 0.2879   |
| 1.3627        | 16.0  | 2400 | 1.3814          | 0.2895   |
| 1.4967        | 17.0  | 2550 | 1.3687          | 0.2895   |
| 1.3997        | 18.0  | 2700 | 1.3565          | 0.2928   |
| 1.2719        | 19.0  | 2850 | 1.3449          | 0.2945   |
| 1.4163        | 20.0  | 3000 | 1.3339          | 0.2978   |
| 1.4           | 21.0  | 3150 | 1.3236          | 0.2995   |
| 1.2918        | 22.0  | 3300 | 1.3138          | 0.3045   |
| 1.3681        | 23.0  | 3450 | 1.3047          | 0.3095   |
| 1.3029        | 24.0  | 3600 | 1.2962          | 0.3111   |
| 1.2697        | 25.0  | 3750 | 1.2880          | 0.3128   |
| 1.2474        | 26.0  | 3900 | 1.2804          | 0.3161   |
| 1.2385        | 27.0  | 4050 | 1.2731          | 0.3195   |
| 1.244         | 28.0  | 4200 | 1.2664          | 0.3245   |
| 1.2831        | 29.0  | 4350 | 1.2599          | 0.3278   |
| 1.3367        | 30.0  | 4500 | 1.2540          | 0.3328   |
| 1.3008        | 31.0  | 4650 | 1.2485          | 0.3361   |
| 1.2529        | 32.0  | 4800 | 1.2434          | 0.3394   |
| 1.3144        | 33.0  | 4950 | 1.2386          | 0.3394   |
| 1.3013        | 34.0  | 5100 | 1.2342          | 0.3394   |
| 1.2892        | 35.0  | 5250 | 1.2301          | 0.3394   |
| 1.2609        | 36.0  | 5400 | 1.2263          | 0.3411   |
| 1.2526        | 37.0  | 5550 | 1.2230          | 0.3444   |
| 1.2445        | 38.0  | 5700 | 1.2199          | 0.3478   |
| 1.2664        | 39.0  | 5850 | 1.2171          | 0.3494   |
| 1.3256        | 40.0  | 6000 | 1.2145          | 0.3494   |
| 1.2237        | 41.0  | 6150 | 1.2124          | 0.3494   |
| 1.251         | 42.0  | 6300 | 1.2104          | 0.3494   |
| 1.1796        | 43.0  | 6450 | 1.2087          | 0.3494   |
| 1.2994        | 44.0  | 6600 | 1.2073          | 0.3478   |
| 1.1956        | 45.0  | 6750 | 1.2062          | 0.3478   |
| 1.2141        | 46.0  | 6900 | 1.2053          | 0.3478   |
| 1.2771        | 47.0  | 7050 | 1.2047          | 0.3478   |
| 1.164         | 48.0  | 7200 | 1.2043          | 0.3478   |
| 1.2779        | 49.0  | 7350 | 1.2041          | 0.3478   |
| 1.2792        | 50.0  | 7500 | 1.2040          | 0.3478   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-large-patch16-224", "model-index": [{"name": "SMIDS_1x_beit_large_SGD_lr00001_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.34775374376039936, "name": "Accuracy"}]}]}]}
transformers pytorch beit image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/beit-large-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us