quangtuyennguyen
commited on
End of training
Browse files- README.md +66 -0
- config.json +36 -0
- model.safetensors +3 -0
- preprocessor_config.json +22 -0
- runs/Nov20_01-34-12_68587df5f397/events.out.tfevents.1732066463.68587df5f397.357.0 +3 -0
- training_args.bin +3 -0
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: google/vit-base-patch16-224-in21k
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: mri_classification_alzheimer_disease
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results: []
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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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# mri_classification_alzheimer_disease
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7795
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- Accuracy: 0.6453
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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: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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- optimizer: Use adamw_torch 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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- num_epochs: 4
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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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| No log | 1.0 | 80 | 0.8764 | 0.5859 |
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| No log | 2.0 | 160 | 0.8594 | 0.5703 |
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| No log | 3.0 | 240 | 0.8095 | 0.6391 |
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| No log | 4.0 | 320 | 0.7795 | 0.6453 |
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### Framework versions
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- Transformers 4.46.3
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- Pytorch 2.5.1+cu121
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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config.json
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{
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"_name_or_path": "google/vit-base-patch16-224-in21k",
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"architectures": [
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"ViTForImageClassification"
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],
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"attention_probs_dropout_prob": 0.0,
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"encoder_stride": 16,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.0,
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"hidden_size": 768,
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"id2label": {
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"0": "Mild_Demented",
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"1": "Moderate_Demented",
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"2": "Non_Demented",
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"3": "Very_Mild_Demented"
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},
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"image_size": 224,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"Mild_Demented": 0,
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"Moderate_Demented": 1,
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"Non_Demented": 2,
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"Very_Mild_Demented": 3
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},
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"layer_norm_eps": 1e-12,
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"model_type": "vit",
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"num_attention_heads": 12,
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"num_channels": 3,
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"num_hidden_layers": 12,
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"patch_size": 16,
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"problem_type": "single_label_classification",
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.46.3"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:944afe03cc5a8347629876503fe00f84610f37bbf5d33bd6e459eb4b03a7ceea
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size 343230128
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preprocessor_config.json
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{
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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0.5,
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0.5,
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0.5
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],
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"image_processor_type": "ViTImageProcessorFast",
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"image_std": [
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0.5,
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0.5,
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0.5
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],
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"resample": 2,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"height": 224,
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"width": 224
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}
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}
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runs/Nov20_01-34-12_68587df5f397/events.out.tfevents.1732066463.68587df5f397.357.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:602834ad150366589bbc98fdbc0288d8aa8469c92ce47206c071b03b2dac47fc
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size 6894
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:11fad44de1ef8f052321abf66acaf931bdc140d29d43d7e5307f366340b89544
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size 5368
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