Upload TFViTForImageClassification
Browse files- README.md +65 -0
- config.json +34 -0
- tf_model.h5 +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_keras_callback
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model-index:
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- name: traynothein_resize_foreclasss
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results: []
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---
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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probably proofread and complete it, then remove this comment. -->
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# traynothein_resize_foreclasss
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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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- Train Loss: 0.0744
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- Train Accuracy: 0.9404
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- Train Top-3-accuracy: 0.9991
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- Validation Loss: 0.2720
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- Validation Accuracy: 0.9431
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- Validation Top-3-accuracy: 0.9991
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- Epoch: 6
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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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- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 658, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
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- training_precision: float32
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### Training results
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| Train Loss | Train Accuracy | Train Top-3-accuracy | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Epoch |
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|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
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| 0.6708 | 0.7378 | 0.9752 | 0.4218 | 0.8246 | 0.9933 | 0 |
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| 0.3109 | 0.8569 | 0.9956 | 0.3083 | 0.8754 | 0.9968 | 1 |
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| 0.2024 | 0.8899 | 0.9975 | 0.2776 | 0.9011 | 0.9979 | 2 |
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| 0.1370 | 0.9104 | 0.9982 | 0.2734 | 0.9170 | 0.9985 | 3 |
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| 0.0996 | 0.9237 | 0.9986 | 0.2775 | 0.9288 | 0.9988 | 4 |
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| 0.0814 | 0.9334 | 0.9989 | 0.2695 | 0.9372 | 0.9990 | 5 |
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| 0.0744 | 0.9404 | 0.9991 | 0.2720 | 0.9431 | 0.9991 | 6 |
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### Framework versions
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- Transformers 4.44.2
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- TensorFlow 2.15.1
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- Datasets 3.0.0
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- Tokenizers 0.19.1
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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": "DR",
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"1": "cataract",
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"2": "glaucoma",
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"3": "normal"
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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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"DR": "0",
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"cataract": "1",
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"glaucoma": "2",
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"normal": "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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"qkv_bias": true,
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"transformers_version": "4.44.2"
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}
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tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:e1187b29817ed00b6d2ed1aad51cb03d3cb2e1822a3ae36565467ca3b44a49be
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size 343475896
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