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
---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_1x_beit_base_sgd_001_fold2
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8635607321131448
---

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# smids_1x_beit_base_sgd_001_fold2

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: 0.3600
- Accuracy: 0.8636

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0974        | 1.0   | 75   | 1.0410          | 0.4309   |
| 1.0056        | 2.0   | 150  | 0.9317          | 0.5424   |
| 0.8916        | 3.0   | 225  | 0.8446          | 0.5890   |
| 0.8349        | 4.0   | 300  | 0.7646          | 0.6473   |
| 0.7414        | 5.0   | 375  | 0.6971          | 0.7022   |
| 0.6784        | 6.0   | 450  | 0.6337          | 0.7571   |
| 0.7121        | 7.0   | 525  | 0.5878          | 0.7754   |
| 0.6558        | 8.0   | 600  | 0.5609          | 0.7787   |
| 0.6317        | 9.0   | 675  | 0.5312          | 0.8087   |
| 0.6518        | 10.0  | 750  | 0.5083          | 0.8136   |
| 0.5234        | 11.0  | 825  | 0.4912          | 0.8203   |
| 0.5342        | 12.0  | 900  | 0.4745          | 0.8236   |
| 0.5263        | 13.0  | 975  | 0.4621          | 0.8186   |
| 0.4728        | 14.0  | 1050 | 0.4552          | 0.8220   |
| 0.4696        | 15.0  | 1125 | 0.4418          | 0.8336   |
| 0.4875        | 16.0  | 1200 | 0.4387          | 0.8286   |
| 0.4719        | 17.0  | 1275 | 0.4281          | 0.8303   |
| 0.4659        | 18.0  | 1350 | 0.4174          | 0.8386   |
| 0.4608        | 19.0  | 1425 | 0.4192          | 0.8319   |
| 0.4678        | 20.0  | 1500 | 0.4085          | 0.8486   |
| 0.4982        | 21.0  | 1575 | 0.4035          | 0.8519   |
| 0.4136        | 22.0  | 1650 | 0.3939          | 0.8552   |
| 0.4205        | 23.0  | 1725 | 0.3934          | 0.8502   |
| 0.45          | 24.0  | 1800 | 0.3901          | 0.8519   |
| 0.4234        | 25.0  | 1875 | 0.3886          | 0.8536   |
| 0.3928        | 26.0  | 1950 | 0.3881          | 0.8486   |
| 0.4665        | 27.0  | 2025 | 0.3799          | 0.8636   |
| 0.416         | 28.0  | 2100 | 0.3843          | 0.8519   |
| 0.386         | 29.0  | 2175 | 0.3779          | 0.8619   |
| 0.3668        | 30.0  | 2250 | 0.3747          | 0.8552   |
| 0.3858        | 31.0  | 2325 | 0.3781          | 0.8602   |
| 0.3907        | 32.0  | 2400 | 0.3740          | 0.8602   |
| 0.4156        | 33.0  | 2475 | 0.3701          | 0.8619   |
| 0.4094        | 34.0  | 2550 | 0.3679          | 0.8619   |
| 0.3888        | 35.0  | 2625 | 0.3683          | 0.8586   |
| 0.3956        | 36.0  | 2700 | 0.3659          | 0.8636   |
| 0.3691        | 37.0  | 2775 | 0.3660          | 0.8636   |
| 0.4229        | 38.0  | 2850 | 0.3645          | 0.8669   |
| 0.308         | 39.0  | 2925 | 0.3651          | 0.8636   |
| 0.382         | 40.0  | 3000 | 0.3644          | 0.8602   |
| 0.4135        | 41.0  | 3075 | 0.3618          | 0.8652   |
| 0.3791        | 42.0  | 3150 | 0.3629          | 0.8636   |
| 0.3729        | 43.0  | 3225 | 0.3622          | 0.8586   |
| 0.3719        | 44.0  | 3300 | 0.3628          | 0.8669   |
| 0.3571        | 45.0  | 3375 | 0.3604          | 0.8636   |
| 0.3721        | 46.0  | 3450 | 0.3598          | 0.8652   |
| 0.381         | 47.0  | 3525 | 0.3604          | 0.8636   |
| 0.3882        | 48.0  | 3600 | 0.3603          | 0.8636   |
| 0.3411        | 49.0  | 3675 | 0.3601          | 0.8636   |
| 0.3299        | 50.0  | 3750 | 0.3600          | 0.8636   |


### Framework versions

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