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# swiftformer-xs-ve-U13-b-80d

This model is a fine-tuned version of [MBZUAI/swiftformer-xs](https://huggingface.co/MBZUAI/swiftformer-xs) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7669
- Accuracy: 0.8261

## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 70

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.92  | 6    | 1.3848          | 0.2174   |
| 1.3838        | 2.0   | 13   | 1.3723          | 0.1957   |
| 1.3838        | 2.92  | 19   | 1.3540          | 0.1739   |
| 1.3023        | 4.0   | 26   | 1.3327          | 0.2391   |
| 1.1398        | 4.92  | 32   | 1.2555          | 0.2391   |
| 1.1398        | 6.0   | 39   | 1.3010          | 0.3913   |
| 1.0076        | 6.92  | 45   | 1.1957          | 0.5      |
| 0.8823        | 8.0   | 52   | 1.0565          | 0.5870   |
| 0.8823        | 8.92  | 58   | 0.9410          | 0.7391   |
| 0.7637        | 10.0  | 65   | 0.9274          | 0.7391   |
| 0.6688        | 10.92 | 71   | 0.8492          | 0.7826   |
| 0.6688        | 12.0  | 78   | 0.8906          | 0.6739   |
| 0.5855        | 12.92 | 84   | 0.8929          | 0.6522   |
| 0.4921        | 14.0  | 91   | 0.8338          | 0.7391   |
| 0.4921        | 14.92 | 97   | 0.7686          | 0.7826   |
| 0.4318        | 16.0  | 104  | 0.8430          | 0.7609   |
| 0.386         | 16.92 | 110  | 0.8315          | 0.7826   |
| 0.386         | 18.0  | 117  | 0.7669          | 0.8261   |
| 0.3483        | 18.92 | 123  | 0.8347          | 0.7174   |
| 0.3023        | 20.0  | 130  | 1.1037          | 0.6304   |
| 0.3023        | 20.92 | 136  | 0.9024          | 0.7174   |
| 0.2973        | 22.0  | 143  | 0.7760          | 0.7826   |
| 0.2973        | 22.92 | 149  | 0.7400          | 0.7826   |
| 0.2529        | 24.0  | 156  | 1.0058          | 0.7174   |
| 0.2086        | 24.92 | 162  | 0.9260          | 0.7609   |
| 0.2086        | 26.0  | 169  | 0.8370          | 0.7174   |
| 0.2265        | 26.92 | 175  | 0.8060          | 0.7391   |
| 0.1942        | 28.0  | 182  | 0.9812          | 0.6957   |
| 0.1942        | 28.92 | 188  | 0.8996          | 0.7391   |
| 0.1708        | 30.0  | 195  | 0.9630          | 0.6957   |
| 0.1747        | 30.92 | 201  | 0.9691          | 0.7174   |
| 0.1747        | 32.0  | 208  | 1.0017          | 0.7391   |
| 0.1461        | 32.92 | 214  | 0.9965          | 0.6957   |
| 0.1457        | 34.0  | 221  | 0.9506          | 0.7391   |
| 0.1457        | 34.92 | 227  | 0.9834          | 0.7391   |
| 0.1814        | 36.0  | 234  | 1.0191          | 0.7609   |
| 0.1383        | 36.92 | 240  | 0.8807          | 0.7609   |
| 0.1383        | 38.0  | 247  | 0.8724          | 0.7609   |
| 0.1718        | 38.92 | 253  | 0.8090          | 0.7391   |
| 0.1289        | 40.0  | 260  | 0.8709          | 0.7609   |
| 0.1289        | 40.92 | 266  | 0.9704          | 0.7391   |
| 0.1193        | 42.0  | 273  | 1.0518          | 0.7391   |
| 0.1193        | 42.92 | 279  | 1.0157          | 0.7174   |
| 0.1224        | 44.0  | 286  | 1.0794          | 0.7391   |
| 0.1104        | 44.92 | 292  | 1.0402          | 0.7391   |
| 0.1104        | 46.0  | 299  | 0.9837          | 0.7609   |
| 0.1055        | 46.92 | 305  | 1.0323          | 0.7174   |
| 0.1242        | 48.0  | 312  | 0.9907          | 0.7391   |
| 0.1242        | 48.92 | 318  | 1.0436          | 0.7609   |
| 0.1283        | 50.0  | 325  | 0.9829          | 0.7391   |
| 0.1035        | 50.92 | 331  | 1.0400          | 0.7174   |
| 0.1035        | 52.0  | 338  | 1.0414          | 0.7174   |
| 0.1066        | 52.92 | 344  | 1.0958          | 0.6957   |
| 0.0863        | 54.0  | 351  | 1.0914          | 0.7174   |
| 0.0863        | 54.92 | 357  | 1.0816          | 0.7174   |
| 0.1062        | 56.0  | 364  | 1.0087          | 0.7174   |
| 0.1214        | 56.92 | 370  | 1.0454          | 0.7391   |
| 0.1214        | 58.0  | 377  | 1.0324          | 0.7391   |
| 0.0984        | 58.92 | 383  | 1.0591          | 0.6739   |
| 0.0966        | 60.0  | 390  | 1.0037          | 0.6957   |
| 0.0966        | 60.92 | 396  | 0.9887          | 0.6957   |
| 0.0626        | 62.0  | 403  | 1.0294          | 0.6739   |
| 0.0626        | 62.92 | 409  | 0.9939          | 0.7174   |
| 0.085         | 64.0  | 416  | 0.9886          | 0.6957   |
| 0.068         | 64.62 | 420  | 1.0773          | 0.6739   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0

avanzada leve moderada no dmae