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---
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: resnet-50-finetuned-student_two_classes
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.85
---
<!-- 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-50-finetuned-student_two_classes
This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4531
- Accuracy: 0.85
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5955 | 1.0 | 13 | 0.4665 | 0.85 |
| 0.5303 | 2.0 | 26 | 0.4790 | 0.85 |
| 0.6127 | 3.0 | 39 | 0.4787 | 0.85 |
| 0.5025 | 4.0 | 52 | 0.4547 | 0.85 |
| 0.471 | 5.0 | 65 | 0.4621 | 0.85 |
| 0.4673 | 6.0 | 78 | 0.4775 | 0.86 |
| 0.4492 | 7.0 | 91 | 0.4648 | 0.86 |
| 0.4144 | 8.0 | 104 | 0.4733 | 0.85 |
| 0.4963 | 9.0 | 117 | 0.4575 | 0.85 |
| 0.4149 | 10.0 | 130 | 0.4691 | 0.85 |
| 0.4588 | 11.0 | 143 | 0.4596 | 0.84 |
| 0.3995 | 12.0 | 156 | 0.4754 | 0.85 |
| 0.359 | 13.0 | 169 | 0.4616 | 0.85 |
| 0.4246 | 14.0 | 182 | 0.4552 | 0.85 |
| 0.4001 | 15.0 | 195 | 0.4839 | 0.85 |
| 0.3919 | 16.0 | 208 | 0.4708 | 0.85 |
| 0.4137 | 17.0 | 221 | 0.4416 | 0.85 |
| 0.3912 | 18.0 | 234 | 0.4507 | 0.85 |
| 0.4322 | 19.0 | 247 | 0.4237 | 0.85 |
| 0.4043 | 20.0 | 260 | 0.4531 | 0.85 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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