This model is a fine-tuned version of mlx-vision/regnet_y_400mf-mlxim on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.3384
Accuracy: 0.8707

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_FUSED 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
0.4107	1.0	74	0.6099	0.6830
0.3186	2.0	148	0.5402	0.7452
0.3731	3.0	222	0.3384	0.8707

Framework versions

Transformers 4.57.1
Pytorch 2.9.0+cpu
Datasets 4.4.1
Tokenizers 0.22.1

yashshinde0080/regnet_y_400mf-mlxim-finetuned-chest_xray-pneumonia

regnet_y_400mf-mlxim-finetuned-chest_xray-pneumonia

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

yashshinde0080/
regnet_y_400mf-mlxim-finetuned-chest_xray-pneumonia