README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - pokemon-classification
metrics:
  - accuracy
model-index:
  - name: my_awesome_pokemon_model_resnet18
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: pokemon-classification
          type: pokemon-classification
          config: full
          split: validation
          args: full
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.01079136690647482

my_awesome_pokemon_model_resnet18

This model is a fine-tuned version of microsoft/resnet-18 on the pokemon-classification dataset. It achieves the following results on the evaluation set:

• Loss: 6.8019
• Accuracy: 0.0108

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: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
4.275	1.0	76	6.1680	0.0014
3.3896	1.99	152	6.6421	0.0115
3.0563	2.99	228	6.8019	0.0108

Framework versions

• Transformers 4.29.1
• Pytorch 2.0.1
• Datasets 2.12.0
• Tokenizers 0.13.3