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library_name: transformers
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- f1
model-index:
- name: resnet-kitchen-object
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.650461837627613
- name: F1
type: f1
value: 0.6481801350383302
---
<!-- 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. -->
# resnet-kitchen-object
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: 1.1453
- Accuracy: 0.6505
- F1: 0.6482
## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 14
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 2.0106 | 1.0 | 224 | 2.3071 | 0.2022 | 0.1647 |
| 1.7945 | 2.0 | 448 | 1.8394 | 0.3369 | 0.3385 |
| 1.6123 | 3.0 | 672 | 1.8258 | 0.3709 | 0.3426 |
| 1.5264 | 4.0 | 896 | 1.7281 | 0.4088 | 0.4060 |
| 1.3383 | 5.0 | 1120 | 1.7189 | 0.4093 | 0.4109 |
| 1.254 | 6.0 | 1344 | 1.4396 | 0.5012 | 0.4885 |
| 1.1198 | 7.0 | 1568 | 1.4400 | 0.5090 | 0.5126 |
| 0.9935 | 8.0 | 1792 | 1.5129 | 0.5177 | 0.5282 |
| 0.8163 | 9.0 | 2016 | 1.2204 | 0.6067 | 0.6020 |
| 0.5996 | 10.0 | 2240 | 1.2234 | 0.6179 | 0.6069 |
| 0.4508 | 11.0 | 2464 | 1.1936 | 0.6354 | 0.6288 |
| 0.3668 | 12.0 | 2688 | 1.1787 | 0.6364 | 0.6313 |
| 0.2702 | 13.0 | 2912 | 1.1435 | 0.6441 | 0.6427 |
| 0.2471 | 14.0 | 3136 | 1.1453 | 0.6505 | 0.6482 |
### Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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