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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: mlx-vision/regnet_y_400mf-mlxim
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tags:
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- generated_from_trainer
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datasets:
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- imagefolder
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metrics:
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- accuracy
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model-index:
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- name: regnet_y_400mf-mlxim-finetuned-chest_xray-pneumonia
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results:
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- task:
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name: Image Classification
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type: image-classification
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dataset:
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name: imagefolder
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type: imagefolder
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config: default
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split: train
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8706896551724138
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# regnet_y_400mf-mlxim-finetuned-chest_xray-pneumonia
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This model is a fine-tuned version of [mlx-vision/regnet_y_400mf-mlxim](https://huggingface.co/mlx-vision/regnet_y_400mf-mlxim) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3384
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- Accuracy: 0.8707
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.4107 | 1.0 | 74 | 0.6099 | 0.6830 |
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| 0.3186 | 2.0 | 148 | 0.5402 | 0.7452 |
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| 0.3731 | 3.0 | 222 | 0.3384 | 0.8707 |
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### Framework versions
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- Transformers 4.57.1
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- Pytorch 2.9.0+cpu
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- Datasets 4.4.1
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- Tokenizers 0.22.1
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