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# SMIDS_10x_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: 0.5991
- Accuracy: 0.7462

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.7934        | 1.0   | 1501  | 0.8533          | 0.5559   |
| 0.6356        | 2.0   | 3002  | 0.7752          | 0.5977   |
| 0.6949        | 3.0   | 4503  | 0.7713          | 0.6093   |
| 0.7187        | 4.0   | 6004  | 0.7641          | 0.6194   |
| 0.6917        | 5.0   | 7505  | 0.7640          | 0.6394   |
| 0.758         | 6.0   | 9006  | 0.7361          | 0.6477   |
| 0.7257        | 7.0   | 10507 | 0.7750          | 0.6110   |
| 0.7254        | 8.0   | 12008 | 0.7896          | 0.5910   |
| 0.7207        | 9.0   | 13509 | 0.7614          | 0.6043   |
| 0.7238        | 10.0  | 15010 | 0.7647          | 0.6194   |
| 0.7523        | 11.0  | 16511 | 0.7391          | 0.6461   |
| 0.7905        | 12.0  | 18012 | 0.7035          | 0.6578   |
| 0.7089        | 13.0  | 19513 | 0.7079          | 0.6427   |
| 0.6601        | 14.0  | 21014 | 0.7170          | 0.6594   |
| 0.6266        | 15.0  | 22515 | 0.7052          | 0.6694   |
| 0.741         | 16.0  | 24016 | 0.6868          | 0.6745   |
| 0.7483        | 17.0  | 25517 | 0.7131          | 0.6711   |
| 0.6898        | 18.0  | 27018 | 0.7515          | 0.6711   |
| 0.7002        | 19.0  | 28519 | 0.7012          | 0.6745   |
| 0.725         | 20.0  | 30020 | 0.7138          | 0.6745   |
| 0.5496        | 21.0  | 31521 | 0.6851          | 0.6995   |
| 0.6544        | 22.0  | 33022 | 0.6736          | 0.6962   |
| 0.6528        | 23.0  | 34523 | 0.7085          | 0.6578   |
| 0.6356        | 24.0  | 36024 | 0.6910          | 0.6828   |
| 0.6672        | 25.0  | 37525 | 0.7351          | 0.6644   |
| 0.6991        | 26.0  | 39026 | 0.7272          | 0.6461   |
| 0.6515        | 27.0  | 40527 | 0.7003          | 0.6878   |
| 0.7263        | 28.0  | 42028 | 0.6530          | 0.7095   |
| 0.5803        | 29.0  | 43529 | 0.6875          | 0.6978   |
| 0.5348        | 30.0  | 45030 | 0.6628          | 0.6945   |
| 0.545         | 31.0  | 46531 | 0.6819          | 0.6878   |
| 0.6304        | 32.0  | 48032 | 0.7101          | 0.6795   |
| 0.6769        | 33.0  | 49533 | 0.6766          | 0.6978   |
| 0.592         | 34.0  | 51034 | 0.6604          | 0.6995   |
| 0.4905        | 35.0  | 52535 | 0.6607          | 0.7095   |
| 0.7431        | 36.0  | 54036 | 0.6616          | 0.7179   |
| 0.6946        | 37.0  | 55537 | 0.6501          | 0.7012   |
| 0.5146        | 38.0  | 57038 | 0.6392          | 0.6995   |
| 0.6008        | 39.0  | 58539 | 0.6484          | 0.7045   |
| 0.6355        | 40.0  | 60040 | 0.6465          | 0.7045   |
| 0.6138        | 41.0  | 61541 | 0.6498          | 0.6978   |
| 0.5115        | 42.0  | 63042 | 0.6591          | 0.7045   |
| 0.5158        | 43.0  | 64543 | 0.6193          | 0.7129   |
| 0.498         | 44.0  | 66044 | 0.6324          | 0.7245   |
| 0.58          | 45.0  | 67545 | 0.6131          | 0.7262   |
| 0.5565        | 46.0  | 69046 | 0.6129          | 0.7329   |
| 0.5501        | 47.0  | 70547 | 0.6023          | 0.7329   |
| 0.4973        | 48.0  | 72048 | 0.6036          | 0.7362   |
| 0.406         | 49.0  | 73549 | 0.5995          | 0.7346   |
| 0.5363        | 50.0  | 75050 | 0.5991          | 0.7462   |


### 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_10x_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": 0.7462437395659433, "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