metadata
library_name: transformers
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: weed_hybrid_transformer
results: []
weed_hybrid_transformer
This model is a fine-tuned version of on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1026
- Accuracy: 0.9667
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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 8.3274 | 1.0 | 150 | 0.8170 | 0.8233 |
| 2.734 | 2.0 | 300 | 0.3290 | 0.9 |
| 2.6813 | 3.0 | 450 | 0.2720 | 0.9167 |
| 1.7794 | 4.0 | 600 | 0.2369 | 0.9067 |
| 1.6344 | 5.0 | 750 | 0.1589 | 0.9567 |
| 1.394 | 6.0 | 900 | 0.1484 | 0.9533 |
| 1.2546 | 7.0 | 1050 | 0.1382 | 0.9567 |
| 1.2253 | 8.0 | 1200 | 0.1565 | 0.9567 |
| 0.7844 | 9.0 | 1350 | 0.1721 | 0.9433 |
| 0.4964 | 10.0 | 1500 | 0.1026 | 0.9667 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.0+cu124
- Datasets 3.0.2
- Tokenizers 0.20.1