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# charger-classif-model

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2678
- Accuracy: 0.9231

## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4057        | 0.0769 | 1    | 0.5508          | 0.6923   |
| 0.5194        | 0.1538 | 2    | 0.5735          | 0.6923   |
| 0.4141        | 0.2308 | 3    | 0.5007          | 0.7692   |
| 0.5442        | 0.3077 | 4    | 0.5160          | 0.8462   |
| 0.43          | 0.3846 | 5    | 0.5931          | 0.7692   |
| 0.4126        | 0.4615 | 6    | 0.5228          | 0.7692   |
| 0.4151        | 0.5385 | 7    | 0.5552          | 0.7692   |
| 0.3753        | 0.6154 | 8    | 0.5825          | 0.6154   |
| 0.3468        | 0.6923 | 9    | 0.5637          | 0.6923   |
| 0.3467        | 0.7692 | 10   | 0.5148          | 0.6923   |
| 0.5188        | 0.8462 | 11   | 0.4735          | 0.7692   |
| 0.4342        | 0.9231 | 12   | 0.5058          | 0.7692   |
| 0.3888        | 1.0    | 13   | 0.5176          | 0.6923   |
| 0.3977        | 1.0769 | 14   | 0.4865          | 0.7692   |
| 0.1799        | 1.1538 | 15   | 0.5299          | 0.6923   |
| 0.4628        | 1.2308 | 16   | 0.5614          | 0.6923   |
| 0.8787        | 1.3077 | 17   | 0.5826          | 0.6923   |
| 0.3396        | 1.3846 | 18   | 0.5337          | 0.7692   |
| 0.2144        | 1.4615 | 19   | 0.5531          | 0.6923   |
| 0.242         | 1.5385 | 20   | 0.5317          | 0.6923   |
| 1.1866        | 1.6154 | 21   | 0.5042          | 0.6923   |
| 0.2689        | 1.6923 | 22   | 0.4067          | 0.8462   |
| 0.3953        | 1.7692 | 23   | 0.4513          | 0.8462   |
| 0.1978        | 1.8462 | 24   | 0.5103          | 0.6923   |
| 0.3293        | 1.9231 | 25   | 0.4829          | 0.6923   |
| 0.3324        | 2.0    | 26   | 0.4915          | 0.8462   |
| 0.2096        | 2.0769 | 27   | 0.5136          | 0.8462   |
| 0.4142        | 2.1538 | 28   | 0.4490          | 0.7692   |
| 0.4267        | 2.2308 | 29   | 0.4697          | 0.7692   |
| 0.1871        | 2.3077 | 30   | 0.4744          | 0.7692   |
| 0.3145        | 2.3846 | 31   | 0.5596          | 0.6923   |
| 0.3417        | 2.4615 | 32   | 0.4589          | 0.6923   |
| 0.1548        | 2.5385 | 33   | 0.5245          | 0.6923   |
| 0.3131        | 2.6154 | 34   | 0.4507          | 0.6923   |
| 0.1974        | 2.6923 | 35   | 0.4068          | 0.8462   |
| 0.3148        | 2.7692 | 36   | 0.5019          | 0.6923   |
| 0.5036        | 2.8462 | 37   | 0.4761          | 0.6923   |
| 0.2178        | 2.9231 | 38   | 0.4132          | 0.9231   |
| 0.4536        | 3.0    | 39   | 0.4745          | 0.7692   |
| 0.3118        | 3.0769 | 40   | 0.4869          | 0.7692   |
| 0.3465        | 3.1538 | 41   | 0.4473          | 0.7692   |
| 0.096         | 3.2308 | 42   | 0.4376          | 0.8462   |
| 0.1726        | 3.3077 | 43   | 0.5971          | 0.7692   |
| 0.1685        | 3.3846 | 44   | 0.4768          | 0.7692   |
| 0.2046        | 3.4615 | 45   | 0.3595          | 0.8462   |
| 0.1297        | 3.5385 | 46   | 0.4701          | 0.7692   |
| 0.4597        | 3.6154 | 47   | 0.4054          | 0.7692   |
| 0.3474        | 3.6923 | 48   | 0.3927          | 0.8462   |
| 0.4476        | 3.7692 | 49   | 0.5063          | 0.8462   |
| 0.1062        | 3.8462 | 50   | 0.4741          | 0.7692   |
| 0.5484        | 3.9231 | 51   | 0.4950          | 0.6923   |
| 0.0945        | 4.0    | 52   | 0.4647          | 0.7692   |
| 0.1053        | 4.0769 | 53   | 0.3743          | 0.8462   |
| 0.4122        | 4.1538 | 54   | 0.4350          | 0.8462   |
| 0.2825        | 4.2308 | 55   | 0.4246          | 0.8462   |
| 0.2912        | 4.3077 | 56   | 0.5250          | 0.6923   |
| 0.3193        | 4.3846 | 57   | 0.3639          | 0.8462   |
| 0.066         | 4.4615 | 58   | 0.3574          | 0.9231   |
| 0.0888        | 4.5385 | 59   | 0.4897          | 0.6923   |
| 0.1046        | 4.6154 | 60   | 0.3032          | 0.9231   |
| 0.2573        | 4.6923 | 61   | 0.5662          | 0.6154   |
| 0.368         | 4.7692 | 62   | 0.3699          | 0.8462   |
| 0.1484        | 4.8462 | 63   | 0.3517          | 0.8462   |
| 0.1444        | 4.9231 | 64   | 0.2988          | 0.9231   |
| 0.1492        | 5.0    | 65   | 0.3523          | 0.8462   |
| 0.112         | 5.0769 | 66   | 0.4245          | 0.8462   |
| 0.0711        | 5.1538 | 67   | 0.4451          | 0.6923   |
| 0.2455        | 5.2308 | 68   | 0.4774          | 0.7692   |
| 0.3981        | 5.3077 | 69   | 0.5084          | 0.7692   |
| 0.1682        | 5.3846 | 70   | 0.4053          | 0.8462   |
| 0.2809        | 5.4615 | 71   | 0.4574          | 0.6923   |
| 0.1929        | 5.5385 | 72   | 0.3242          | 0.7692   |
| 0.161         | 5.6154 | 73   | 0.3854          | 0.7692   |
| 0.1475        | 5.6923 | 74   | 0.3935          | 0.7692   |
| 0.1058        | 5.7692 | 75   | 0.5751          | 0.6923   |
| 0.1103        | 5.8462 | 76   | 0.3874          | 0.8462   |
| 0.1057        | 5.9231 | 77   | 0.3984          | 0.7692   |
| 0.1593        | 6.0    | 78   | 0.3299          | 0.8462   |
| 0.1154        | 6.0769 | 79   | 0.4778          | 0.7692   |
| 0.3131        | 6.1538 | 80   | 0.4863          | 0.7692   |
| 0.0791        | 6.2308 | 81   | 0.4897          | 0.7692   |
| 0.0635        | 6.3077 | 82   | 0.5831          | 0.7692   |
| 0.0704        | 6.3846 | 83   | 0.4384          | 0.8462   |
| 0.0597        | 6.4615 | 84   | 0.5519          | 0.7692   |
| 0.1117        | 6.5385 | 85   | 0.4525          | 0.7692   |
| 0.1542        | 6.6154 | 86   | 0.5354          | 0.8462   |
| 0.5737        | 6.6923 | 87   | 0.5034          | 0.7692   |
| 0.4216        | 6.7692 | 88   | 0.4514          | 0.7692   |
| 0.3276        | 6.8462 | 89   | 0.5688          | 0.7692   |
| 0.119         | 6.9231 | 90   | 0.3433          | 0.9231   |
| 0.1519        | 7.0    | 91   | 0.4454          | 0.7692   |
| 0.1155        | 7.0769 | 92   | 0.3323          | 0.7692   |
| 0.1264        | 7.1538 | 93   | 0.4030          | 0.6923   |
| 0.0585        | 7.2308 | 94   | 0.3404          | 0.8462   |
| 0.1404        | 7.3077 | 95   | 0.3507          | 0.8462   |
| 0.0417        | 7.3846 | 96   | 0.4860          | 0.7692   |
| 0.0873        | 7.4615 | 97   | 0.4896          | 0.8462   |
| 0.0801        | 7.5385 | 98   | 0.4383          | 0.7692   |
| 0.2163        | 7.6154 | 99   | 0.3764          | 0.8462   |
| 0.1823        | 7.6923 | 100  | 0.4258          | 0.8462   |
| 0.1832        | 7.7692 | 101  | 0.2890          | 0.8462   |
| 0.0879        | 7.8462 | 102  | 0.2909          | 0.8462   |
| 0.2345        | 7.9231 | 103  | 0.3617          | 0.8462   |
| 0.1096        | 8.0    | 104  | 0.2678          | 0.9231   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.6.0+cpu
- Datasets 3.2.0
- Tokenizers 0.21.0

healthy broken