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# SMIDS_1x_beit_large_RMSProp_lr001_fold1

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: 0.8097
- Accuracy: 0.7245

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.896         | 1.0   | 151  | 0.9563          | 0.4891   |
| 0.825         | 2.0   | 302  | 0.8862          | 0.4992   |
| 0.9111        | 3.0   | 453  | 0.8464          | 0.5392   |
| 0.906         | 4.0   | 604  | 1.1323          | 0.5008   |
| 0.8445        | 5.0   | 755  | 0.8163          | 0.5543   |
| 0.7898        | 6.0   | 906  | 0.7974          | 0.5726   |
| 0.877         | 7.0   | 1057 | 0.8031          | 0.5576   |
| 0.7394        | 8.0   | 1208 | 0.8318          | 0.5376   |
| 0.8121        | 9.0   | 1359 | 0.8937          | 0.5209   |
| 0.782         | 10.0  | 1510 | 0.8151          | 0.5509   |
| 0.7145        | 11.0  | 1661 | 0.7700          | 0.5776   |
| 0.705         | 12.0  | 1812 | 0.7647          | 0.6411   |
| 0.7316        | 13.0  | 1963 | 0.7858          | 0.6277   |
| 0.6786        | 14.0  | 2114 | 0.7187          | 0.6895   |
| 0.713         | 15.0  | 2265 | 0.8614          | 0.6361   |
| 0.6322        | 16.0  | 2416 | 1.1875          | 0.5459   |
| 0.6417        | 17.0  | 2567 | 0.7143          | 0.6611   |
| 0.5716        | 18.0  | 2718 | 0.6837          | 0.6912   |
| 0.7126        | 19.0  | 2869 | 0.6743          | 0.6995   |
| 0.5146        | 20.0  | 3020 | 0.7104          | 0.6962   |
| 0.6372        | 21.0  | 3171 | 0.8025          | 0.6344   |
| 0.591         | 22.0  | 3322 | 0.7366          | 0.6745   |
| 0.5767        | 23.0  | 3473 | 0.7199          | 0.6845   |
| 0.6216        | 24.0  | 3624 | 0.6446          | 0.7162   |
| 0.4821        | 25.0  | 3775 | 0.6762          | 0.7312   |
| 0.4997        | 26.0  | 3926 | 0.7727          | 0.6978   |
| 0.4709        | 27.0  | 4077 | 0.6575          | 0.7145   |
| 0.6167        | 28.0  | 4228 | 0.7514          | 0.6878   |
| 0.5841        | 29.0  | 4379 | 0.7254          | 0.6895   |
| 0.5191        | 30.0  | 4530 | 0.6860          | 0.7078   |
| 0.4562        | 31.0  | 4681 | 0.6929          | 0.6895   |
| 0.4866        | 32.0  | 4832 | 0.6766          | 0.7045   |
| 0.461         | 33.0  | 4983 | 0.6768          | 0.7129   |
| 0.4542        | 34.0  | 5134 | 0.6792          | 0.7162   |
| 0.4396        | 35.0  | 5285 | 0.7670          | 0.6945   |
| 0.4895        | 36.0  | 5436 | 0.7161          | 0.7195   |
| 0.4944        | 37.0  | 5587 | 0.6736          | 0.7179   |
| 0.4542        | 38.0  | 5738 | 0.7404          | 0.7078   |
| 0.4109        | 39.0  | 5889 | 0.6768          | 0.7362   |
| 0.4524        | 40.0  | 6040 | 0.6754          | 0.7179   |
| 0.5153        | 41.0  | 6191 | 0.7039          | 0.7179   |
| 0.4222        | 42.0  | 6342 | 0.7249          | 0.7179   |
| 0.3565        | 43.0  | 6493 | 0.7081          | 0.7262   |
| 0.3442        | 44.0  | 6644 | 0.7229          | 0.7212   |
| 0.3456        | 45.0  | 6795 | 0.7268          | 0.7329   |
| 0.3115        | 46.0  | 6946 | 0.7612          | 0.7279   |
| 0.377         | 47.0  | 7097 | 0.7447          | 0.7362   |
| 0.342         | 48.0  | 7248 | 0.7978          | 0.7312   |
| 0.3421        | 49.0  | 7399 | 0.8076          | 0.7262   |
| 0.2457        | 50.0  | 7550 | 0.8097          | 0.7245   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1

{"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_RMSProp_lr001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7245409015025042, "name": "Accuracy"}]}]}]}
transformers safetensors 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