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---
library_name: transformers
base_model: juliensimon/autotrain-chest-xray-demo-1677859324
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: autotrain-chest-xray-demo-1677859324-finetuned-eurosat
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: 0.9712643678160919
---
<!-- 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. -->
# autotrain-chest-xray-demo-1677859324-finetuned-eurosat
This model is a fine-tuned version of [juliensimon/autotrain-chest-xray-demo-1677859324](https://huggingface.co/juliensimon/autotrain-chest-xray-demo-1677859324) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0731
- Accuracy: 0.9713
## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.268 | 0.9796 | 36 | 0.0862 | 0.9617 |
| 0.1635 | 1.9796 | 72 | 0.0767 | 0.9674 |
| 0.1039 | 2.9796 | 108 | 0.0731 | 0.9713 |
### Framework versions
- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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