Training in progress epoch 0

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_keras_callback
+model-index:
+- name: SuperMaker/vit-base-patch16-224-in21k-luekemia
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information Keras had access to. You should
+probably proofread and complete it, then remove this comment. -->
+
+# SuperMaker/vit-base-patch16-224-in21k-luekemia
+
+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.
+It achieves the following results on the evaluation set:
+- Train Loss: 0.5007
+- Train Accuracy: 0.7629
+- Validation Loss: 0.7206
+- Validation Accuracy: 0.6643
+- Epoch: 0
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- optimizer: {'inner_optimizer': {'module': 'keras.optimizers.experimental', 'class_name': 'SGD', 'config': {'name': 'SGD', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': 1, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'CosineDecay', 'config': {'initial_learning_rate': 0.001, 'decay_steps': 896, 'alpha': 0.0, 'name': None, 'warmup_target': None, 'warmup_steps': 0}, 'registered_name': None}, 'momentum': 0.9, 'nesterov': False}, 'registered_name': None}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
+- training_precision: mixed_float16
+
+### Training results
+
+| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
+|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
+| 0.5007     | 0.7629         | 0.7206          | 0.6643              | 0     |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- TensorFlow 2.13.0
+- Datasets 2.1.0
+- Tokenizers 0.14.1

config.json

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+{
+  "_name_or_path": "google/vit-base-patch16-224-in21k",
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "hem",
+    "1": "all"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "all": 1,
+    "hem": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "qkv_bias": true,
+  "transformers_version": "4.35.0"
+}

logs/train/events.out.tfevents.1701545954.49fb5efe728d.149.0.v2

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tf_model.h5

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