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cat_dog_classifier_with_small_datasest

Image Classification
Transformers
Safetensors
resnet
Generated from Trainer
Eval Results
Inference Endpoints
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metadata
library_name: transformers
license: apache-2.0
base_model: microsoft/resnet-50
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: cat_dog_classifier_with_small_datasest
    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: 0.95

cat_dog_classifier_with_small_datasest

This model is a fine-tuned version of microsoft/resnet-50 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1369
  • Accuracy: 0.95

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: 4e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use 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_steps: 500
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 70 0.5422 0.8571
No log 2.0 140 0.5221 0.8786
No log 3.0 210 0.4977 0.8571
No log 4.0 280 0.4617 0.8786
No log 5.0 350 0.3932 0.9143
No log 6.0 420 0.3411 0.9143
No log 7.0 490 0.2884 0.9143
0.4971 8.0 560 0.2429 0.9286
0.4971 9.0 630 0.2151 0.9429
0.4971 10.0 700 0.1962 0.9286
0.4971 11.0 770 0.1727 0.9357
0.4971 12.0 840 0.1676 0.95
0.4971 13.0 910 0.1764 0.9286
0.4971 14.0 980 0.1565 0.9429
0.2878 15.0 1050 0.1578 0.9429
0.2878 16.0 1120 0.1577 0.9429
0.2878 17.0 1190 0.1393 0.9429
0.2878 18.0 1260 0.1472 0.9429
0.2878 19.0 1330 0.1315 0.95
0.2878 20.0 1400 0.1369 0.95

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.4.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0