metadata
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
datasets:
- chest-xray-classification
metrics:
- accuracy
model-index:
- name: Cheese_xray
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: chest-xray-classification
type: chest-xray-classification
config: full
split: test
args: full
metrics:
- name: Accuracy
type: accuracy
value: 0.7061855670103093
Cheese_xray
This model is a fine-tuned version of microsoft/resnet-50 on the chest-xray-classification dataset. It achieves the following results on the evaluation set:
- Loss: 0.4278
- Accuracy: 0.7062
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5547 | 0.99 | 63 | 0.5554 | 0.7062 |
| 0.4303 | 1.99 | 127 | 0.4387 | 0.7079 |
| 0.4377 | 2.96 | 189 | 0.4278 | 0.7062 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0