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# resnet-50-finetuned-pokemon-finetuned-pokemon

This model is a fine-tuned version of [TeeA/resnet-50-finetuned-pokemon](https://huggingface.co/TeeA/resnet-50-finetuned-pokemon) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 14.1746
- Accuracy: 0.0849

## 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: 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: 0.1
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1894        | 0.99  | 38   | 9.2115          | 0.0137   |
| 1.1389        | 1.99  | 76   | 9.2521          | 0.0129   |
| 1.0432        | 2.98  | 114  | 9.4765          | 0.0144   |
| 1.0625        | 4.0   | 153  | 9.7668          | 0.0137   |
| 1.0805        | 4.99  | 191  | 10.2526         | 0.0137   |
| 1.0353        | 5.99  | 229  | 10.3238         | 0.0129   |
| 0.9747        | 6.98  | 267  | 10.5779         | 0.0165   |
| 0.9708        | 8.0   | 306  | 10.7458         | 0.0180   |
| 0.8886        | 8.99  | 344  | 11.0072         | 0.0194   |
| 0.8408        | 9.99  | 382  | 11.3171         | 0.0223   |
| 0.802         | 10.98 | 420  | 11.5545         | 0.0245   |
| 0.7903        | 12.0  | 459  | 11.7722         | 0.0288   |
| 0.7553        | 12.99 | 497  | 11.9834         | 0.0353   |
| 0.7413        | 13.99 | 535  | 11.9815         | 0.0446   |
| 0.6272        | 14.98 | 573  | 12.0871         | 0.0496   |
| 0.6944        | 16.0  | 612  | 12.3713         | 0.0590   |
| 0.6322        | 16.99 | 650  | 12.6826         | 0.0554   |
| 0.6131        | 17.99 | 688  | 12.4819         | 0.0612   |
| 0.5916        | 18.98 | 726  | 12.6246         | 0.0647   |
| 0.5094        | 20.0  | 765  | 12.6641         | 0.0669   |
| 0.5201        | 20.99 | 803  | 12.8861         | 0.0662   |
| 0.4731        | 21.99 | 841  | 12.7431         | 0.0655   |
| 0.5132        | 22.98 | 879  | 12.7786         | 0.0705   |
| 0.5036        | 24.0  | 918  | 12.9990         | 0.0727   |
| 0.4863        | 24.99 | 956  | 13.0419         | 0.0727   |
| 0.4852        | 25.99 | 994  | 13.0573         | 0.0734   |
| 0.4983        | 26.98 | 1032 | 13.1310         | 0.0719   |
| 0.459         | 28.0  | 1071 | 13.0688         | 0.0748   |
| 0.4556        | 28.99 | 1109 | 13.4128         | 0.0748   |
| 0.4729        | 29.99 | 1147 | 13.3530         | 0.0741   |
| 0.4659        | 30.98 | 1185 | 13.2308         | 0.0763   |
| 0.4337        | 32.0  | 1224 | 13.3264         | 0.0748   |
| 0.456         | 32.99 | 1262 | 13.3506         | 0.0741   |
| 0.4423        | 33.99 | 1300 | 13.3607         | 0.0784   |
| 0.4037        | 34.98 | 1338 | 13.2521         | 0.0734   |
| 0.3891        | 36.0  | 1377 | 13.3702         | 0.0777   |
| 0.3992        | 36.99 | 1415 | 13.4762         | 0.0777   |
| 0.4014        | 37.99 | 1453 | 13.5382         | 0.0791   |
| 0.3549        | 38.98 | 1491 | 13.5550         | 0.0791   |
| 0.4048        | 40.0  | 1530 | 13.6406         | 0.0799   |
| 0.3711        | 40.99 | 1568 | 13.5120         | 0.0777   |
| 0.3834        | 41.99 | 1606 | 13.9230         | 0.0799   |
| 0.3475        | 42.98 | 1644 | 13.8602         | 0.0791   |
| 0.3465        | 44.0  | 1683 | 13.6931         | 0.0806   |
| 0.3682        | 44.99 | 1721 | 13.7774         | 0.0784   |
| 0.3613        | 45.99 | 1759 | 14.0235         | 0.0791   |
| 0.368         | 46.98 | 1797 | 13.9289         | 0.0813   |
| 0.3961        | 48.0  | 1836 | 14.2549         | 0.0806   |
| 0.365         | 48.99 | 1874 | 14.1114         | 0.0813   |
| 0.3259        | 49.99 | 1912 | 13.9710         | 0.0806   |
| 0.2998        | 50.98 | 1950 | 14.0288         | 0.0806   |
| 0.3203        | 52.0  | 1989 | 13.9398         | 0.0813   |
| 0.3104        | 52.99 | 2027 | 14.0255         | 0.0820   |
| 0.3232        | 53.99 | 2065 | 13.9355         | 0.0827   |
| 0.3521        | 54.98 | 2103 | 13.8627         | 0.0806   |
| 0.3322        | 56.0  | 2142 | 14.0179         | 0.0806   |
| 0.3129        | 56.99 | 2180 | 13.9640         | 0.0820   |
| 0.3159        | 57.99 | 2218 | 14.1997         | 0.0799   |
| 0.3118        | 58.98 | 2256 | 14.1639         | 0.0820   |
| 0.3196        | 60.0  | 2295 | 14.0334         | 0.0806   |
| 0.301         | 60.99 | 2333 | 13.9954         | 0.0820   |
| 0.3142        | 61.99 | 2371 | 14.1432         | 0.0799   |
| 0.3192        | 62.98 | 2409 | 14.0269         | 0.0784   |
| 0.3342        | 64.0  | 2448 | 14.0450         | 0.0806   |
| 0.3045        | 64.99 | 2486 | 14.1746         | 0.0849   |
| 0.2991        | 65.99 | 2524 | 14.3192         | 0.0806   |
| 0.3228        | 66.98 | 2562 | 14.1782         | 0.0784   |
| 0.2711        | 68.0  | 2601 | 14.4261         | 0.0849   |
| 0.2473        | 68.99 | 2639 | 14.2303         | 0.0827   |
| 0.3287        | 69.99 | 2677 | 14.2750         | 0.0827   |
| 0.2673        | 70.98 | 2715 | 14.2303         | 0.0820   |
| 0.2843        | 72.0  | 2754 | 14.4086         | 0.0806   |
| 0.3099        | 72.99 | 2792 | 14.5184         | 0.0827   |
| 0.3102        | 73.99 | 2830 | 14.2768         | 0.0835   |
| 0.2911        | 74.98 | 2868 | 14.1010         | 0.0835   |
| 0.2927        | 76.0  | 2907 | 14.4618         | 0.0813   |
| 0.2967        | 76.99 | 2945 | 14.3581         | 0.0820   |
| 0.2446        | 77.99 | 2983 | 14.4562         | 0.0835   |
| 0.3035        | 78.98 | 3021 | 14.2681         | 0.0835   |
| 0.2989        | 80.0  | 3060 | 14.2768         | 0.0827   |
| 0.2486        | 80.99 | 3098 | 14.4242         | 0.0820   |
| 0.2622        | 81.99 | 3136 | 14.3810         | 0.0835   |
| 0.2892        | 82.98 | 3174 | 14.4637         | 0.0827   |
| 0.2668        | 84.0  | 3213 | 14.4597         | 0.0835   |
| 0.2527        | 84.99 | 3251 | 14.3098         | 0.0820   |
| 0.2636        | 85.99 | 3289 | 14.3741         | 0.0835   |
| 0.247         | 86.98 | 3327 | 14.5369         | 0.0842   |
| 0.2693        | 88.0  | 3366 | 14.4039         | 0.0835   |
| 0.2692        | 88.99 | 3404 | 14.6161         | 0.0835   |
| 0.28          | 89.99 | 3442 | 14.5244         | 0.0835   |
| 0.2535        | 90.98 | 3480 | 14.4062         | 0.0842   |
| 0.2887        | 92.0  | 3519 | 14.4113         | 0.0806   |
| 0.257         | 92.99 | 3557 | 14.3442         | 0.0842   |
| 0.2627        | 93.99 | 3595 | 14.4693         | 0.0835   |
| 0.2804        | 94.98 | 3633 | 14.3223         | 0.0835   |
| 0.2529        | 96.0  | 3672 | 14.3844         | 0.0835   |
| 0.2327        | 96.99 | 3710 | 14.4284         | 0.0835   |
| 0.2643        | 97.99 | 3748 | 14.5567         | 0.0835   |
| 0.284         | 98.98 | 3786 | 14.6738         | 0.0813   |
| 0.2503        | 99.35 | 3800 | 14.5363         | 0.0842   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

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