convnext-tiny-finetuned-dogfood
This model is a fine-tuned version of facebook/convnext-tiny-224 on the lewtun/dog_food dataset. It achieves the following results on the evaluation set:
- Loss: 0.9277
- Accuracy: 0.7253
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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0681 | 1.0 | 16 | 0.9125 | 0.7422 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
- Downloads last month
- 6
This model does not have enough activity to be deployed to Inference API (serverless) yet.
Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Dataset used to train abhishek/convnext-tiny-finetuned-dogfood
Evaluation results
- Accuracy on lewtun/dog_foodself-reported0.725
- Accuracy on lewtun/dog_foodtest set self-reported0.687
- Precision Macro on lewtun/dog_foodtest set self-reported0.718
- Precision Micro on lewtun/dog_foodtest set self-reported0.687
- Precision Weighted on lewtun/dog_foodtest set self-reported0.724
- Recall Macro on lewtun/dog_foodtest set self-reported0.701
- Recall Micro on lewtun/dog_foodtest set self-reported0.687
- Recall Weighted on lewtun/dog_foodtest set self-reported0.687
- F1 Macro on lewtun/dog_foodtest set self-reported0.669
- F1 Micro on lewtun/dog_foodtest set self-reported0.687