---
library_name: transformers
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: weed_hybrid_transformer
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# weed_hybrid_transformer

This model is a fine-tuned version of [](https://huggingface.co/) 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