Model save
Browse files
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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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: finetuned-Leukemia-cell
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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: 0.9548872180451128
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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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# finetuned-Leukemia-cell
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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 the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1823
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- Accuracy: 0.9549
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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: 0.0002
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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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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- num_epochs: 4
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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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| 0.4862 | 1.49 | 100 | 0.4092 | 0.9173 |
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| 0.2095 | 2.99 | 200 | 0.1823 | 0.9549 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu118
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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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": "LLA",
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"1": "folicular",
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"2": "linfos normales",
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"3": "llc",
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"4": "marginal",
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"5": "mononucleosis",
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"6": "trico"
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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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"LLA": "0",
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"folicular": "1",
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"linfos normales": "2",
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"llc": "3",
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"marginal": "4",
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"mononucleosis": "5",
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"trico": "6"
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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": "4.35.2"
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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 sha256:5a995b7567cdb05dfd9c3fa30e3aa0d7d8620e2d8c6b3206adc2af55a77badef
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size 343239356
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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": "ViTFeatureExtractor",
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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/Nov30_22-49-16_6c26dad0aabb/events.out.tfevents.1701384598.6c26dad0aabb.7066.0
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version https://git-lfs.github.com/spec/v1
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size 4432
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runs/Nov30_22-57-39_6c26dad0aabb/events.out.tfevents.1701385071.6c26dad0aabb.7066.1
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version https://git-lfs.github.com/spec/v1
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size 9472
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:98f8a3a2f49f3b298aa444fc183b1fa523ebc06d66cf841ca5da0708719ef5cb
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size 4600
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