cmmy / README.md
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metadata
library_name: transformers
license: apache-2.0
base_model: therealcyberlord/stanford-car-vit-patch16
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: cmmy
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.541167345355827

cmmy

This model is a fine-tuned version of therealcyberlord/stanford-car-vit-patch16 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Accuracy: 0.5412
  • Loss: 1.4404

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: 0.001
  • train_batch_size: 256
  • eval_batch_size: 256
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 1024
  • 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
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10

Training results

Training Loss Epoch Step Accuracy Validation Loss
16.0903 0.9967 226 0.1969 3.4455
11.5438 1.9967 452 0.2992 2.4033
9.5963 2.9967 678 0.3492 2.0761
8.3873 3.9967 904 0.3934 1.8921
7.3127 4.9967 1130 0.4288 1.7535
6.2178 5.9967 1356 0.4609 1.6533
5.4619 6.9967 1582 0.4856 1.5859
4.618 7.9967 1808 0.5129 1.5253
3.9349 8.9967 2034 0.5315 1.4693
3.4667 9.9967 2260 0.5412 1.4404

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0