Training in progress epoch 0

README.md

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+---
+license: apache-2.0
+base_model: microsoft/resnet-50
+tags:
+- generated_from_keras_callback
+model-index:
+- name: SaladSlayer00/new_model
+  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. -->
+
+# SaladSlayer00/new_model
+
+This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Train Loss: 7.0706
+- Validation Loss: 4.8379
+- Validation Accuracy: 0.0167
+- 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: {'name': 'AdamWeightDecay', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
+- training_precision: float32
+
+### Training results
+
+| Train Loss | Validation Loss | Validation Accuracy | Epoch |
+|:----------:|:---------------:|:-------------------:|:-----:|
+| 7.0706     | 4.8379          | 0.0167              | 0     |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- TensorFlow 2.15.0
+- Datasets 2.16.0
+- Tokenizers 0.15.0

logs/train/events.out.tfevents.1703696915.fv-az1118-740.1877.0.v2

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logs/validation/events.out.tfevents.1703698507.fv-az1118-740.1877.1.v2

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preprocessor_config.json

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+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "feature_extractor_type": "ConvNextFeatureExtractor",
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextFeatureExtractor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}

tf_model.h5

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