Patacognition
Collection
All ViTs, datasets and spaces created for the sole purpose of patacón recognition.
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8 items
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Updated
focal-patacotron
This model is a fine-tuned version of microsoft/focalnet-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0897
- Accuracy: 0.9659
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0575 | 0.97 | 24 | 0.1208 | 0.9545 |
| 0.0275 | 1.94 | 48 | 0.0897 | 0.9659 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.1
- Tokenizers 0.13.3
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Model tree for frncscp/focalnet-small-patacon
Base model
microsoft/focalnet-small