dhritic99/model99123
Browse files- README.md +66 -0
- all_results.json +13 -0
- config.json +36 -0
- eval_results.json +8 -0
- model.safetensors +3 -0
- preprocessor_config.json +22 -0
- train_results.json +8 -0
- trainer_state.json +344 -0
- training_args.bin +3 -0
README.md
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---
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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: vit-base-brain-tumor-detection2
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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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# vit-base-brain-tumor-detection2
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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: 0.3987
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- Accuracy: 0.8883
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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-06
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 64
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 1000
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- num_epochs: 30
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- mixed_precision_training: Native AMP
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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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| 0.8758 | 7.8125 | 500 | 0.8912 | 0.6182 |
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| 0.5256 | 15.625 | 1000 | 0.6332 | 0.7607 |
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| 0.2247 | 23.4375 | 1500 | 0.3877 | 0.8936 |
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### Framework versions
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- Transformers 4.42.4
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- Pytorch 2.3.1+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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all_results.json
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{
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"epoch": 30.0,
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"eval_accuracy": 0.88828125,
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"eval_loss": 0.3986928462982178,
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"eval_runtime": 7.6565,
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"eval_samples_per_second": 167.177,
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"eval_steps_per_second": 20.897,
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"total_flos": 9.52238637305561e+18,
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"train_loss": 0.5872499863306682,
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"train_runtime": 1494.2494,
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"train_samples_per_second": 82.235,
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"train_steps_per_second": 1.285
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}
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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": "LABEL_0",
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"1": "LABEL_1",
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"2": "LABEL_2",
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"3": "LABEL_3"
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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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"LABEL_0": 0,
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"LABEL_1": 1,
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"LABEL_2": 2,
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"LABEL_3": 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": "4.42.4"
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}
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eval_results.json
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{
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"epoch": 30.0,
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"eval_accuracy": 0.88828125,
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"eval_loss": 0.3986928462982178,
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"eval_runtime": 7.6565,
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"eval_samples_per_second": 167.177,
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"eval_steps_per_second": 20.897
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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:cbf1e12fe46cca4adcfbdf946fa368982fc17439f924effe56dad07803f2fd37
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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": "ViTImageProcessor",
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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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train_results.json
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{
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"epoch": 30.0,
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"total_flos": 9.52238637305561e+18,
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"train_loss": 0.5872499863306682,
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"train_runtime": 1494.2494,
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"train_samples_per_second": 82.235,
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"train_steps_per_second": 1.285
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}
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trainer_state.json
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