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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: resnet-50-bottomCleanedData
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: 0.8342792281498297
---
<!-- 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-bottomCleanedData
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: 0.4809
- Accuracy: 0.8343
## 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: 7
- total_train_batch_size: 56
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3235 | 1.0 | 141 | 1.3266 | 0.5096 |
| 1.1546 | 2.0 | 283 | 1.1380 | 0.5153 |
| 0.9412 | 2.99 | 424 | 0.8690 | 0.6515 |
| 0.8539 | 4.0 | 566 | 0.6672 | 0.7594 |
| 0.7967 | 4.99 | 707 | 0.6256 | 0.7503 |
| 0.7679 | 6.0 | 849 | 0.5357 | 0.8229 |
| 0.7265 | 7.0 | 991 | 0.5698 | 0.7832 |
| 0.7395 | 8.0 | 1132 | 0.5125 | 0.8161 |
| 0.7029 | 9.0 | 1274 | 0.4993 | 0.8150 |
| 0.7275 | 9.96 | 1410 | 0.4809 | 0.8343 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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