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# Pokemon-classification-1stGen-DataAug

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4623
- F1: 0.8973

## 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: 6.56462271373806e-05
- train_batch_size: 4
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 9

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.525         | 1.0   | 527  | 3.6420          | 0.4635 |
| 2.6921        | 2.0   | 1055 | 2.0075          | 0.6360 |
| 1.4828        | 3.0   | 1582 | 1.2151          | 0.7582 |
| 0.9262        | 4.0   | 2110 | 0.8820          | 0.8297 |
| 0.6285        | 5.0   | 2637 | 0.6866          | 0.8734 |
| 0.4634        | 6.0   | 3165 | 0.5699          | 0.8854 |
| 0.3683        | 7.0   | 3692 | 0.5223          | 0.8913 |
| 0.3268        | 8.0   | 4220 | 0.4702          | 0.8967 |
| 0.2839        | 8.99  | 4743 | 0.4623          | 0.8973 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.2.0.dev20231126+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

abra aerodactyl butterfree ponyta porygon primeape psyduck raichu rapidash raticate rattata rhydon rhyhorn caterpie sandshrew sandslash scyther seadra seaking seel shellder slowbro slowpoke snorlax chansey spearow squirtle starmie staryu tangela tauros tentacool tentacruel vaporeon venomoth charizard venonat venusaur victreebel vileplume voltorb vulpix wartortle weedle weepinbell weezing charmander wigglytuff zapdos zubat charmeleon clefable clefairy cloyster cubone alakazam dewgong diglett ditto dodrio doduo dragonair dragonite dratini drowzee dugtrio arbok eevee ekans electabuzz electrode exeggcute exeggutor farfetchd fearow flareon gastly arcanine gengar geodude gloom golbat goldeen golduck graveler grimer growlithe gyarados articuno haunter hitmonchan hitmonlee horsea hypno ivysaur jigglypuff jolteon jynx kabutops beedrill kadabra kakuna kangaskhan kingler koffing lapras lickitung machamp machoke machop bellsprout magikarp magmar magnemite magneton mankey marowak meowth metapod mew mewtwo blastoise moltres mr. mime mrmime nidoking nidoqueen nidorina nidorino ninetales oddish omanyte bulbasaur omastar parasect pidgeot pidgeotto pidgey pikachu pinsir poliwag poliwhirl poliwrath