End of training

README.md

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+---
+license: other
+tags:
+- generated_from_keras_callback
+model-index:
+- name: Xanadu00/galaxy_classifier_mobilevit_3
+  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. -->
+
+# Xanadu00/galaxy_classifier_mobilevit_3
+
+This model is a fine-tuned version of [apple/mobilevit-small](https://huggingface.co/apple/mobilevit-small) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Train Loss: 0.1914
+- Train Accuracy: 0.9341
+- Validation Loss: 0.5148
+- Validation Accuracy: 0.8512
+- Epoch: 16
+
+## 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': 'AdamW', 'weight_decay': 0.01, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'ExponentialDecay', 'config': {'initial_learning_rate': 0.002, 'decay_steps': 10000, 'decay_rate': 0.01, 'staircase': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
+- training_precision: float32
+
+### Training results
+
+| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
+|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
+| 1.1049     | 0.6128         | 0.7422          | 0.7517              | 0     |
+| 0.7149     | 0.7564         | 0.6376          | 0.7821              | 1     |
+| 0.6080     | 0.7945         | 0.6947          | 0.7745              | 2     |
+| 0.5376     | 0.8160         | 0.5589          | 0.8134              | 3     |
+| 0.4977     | 0.8279         | 0.5458          | 0.8162              | 4     |
+| 0.4564     | 0.8407         | 0.4799          | 0.8441              | 5     |
+| 0.4271     | 0.8557         | 0.4765          | 0.8413              | 6     |
+| 0.3957     | 0.8619         | 0.4790          | 0.8453              | 7     |
+| 0.3701     | 0.8741         | 0.5376          | 0.8329              | 8     |
+| 0.3425     | 0.8829         | 0.4359          | 0.8619              | 9     |
+| 0.3192     | 0.8892         | 0.4475          | 0.8585              | 10    |
+| 0.2972     | 0.8967         | 0.4143          | 0.8712              | 11    |
+| 0.2691     | 0.9080         | 0.4819          | 0.8498              | 12    |
+| 0.2445     | 0.9144         | 0.4543          | 0.8563              | 13    |
+| 0.2261     | 0.9220         | 0.4221          | 0.8689              | 14    |
+| 0.2127     | 0.9251         | 0.5076          | 0.8540              | 15    |
+| 0.1914     | 0.9341         | 0.5148          | 0.8512              | 16    |
+
+
+### Framework versions
+
+- Transformers 4.30.2
+- TensorFlow 2.12.0
+- Datasets 2.13.1
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "apple/mobilevit-small",
+  "architectures": [
+    "MobileViTForImageClassification"
+  ],
+  "aspp_dropout_prob": 0.1,
+  "aspp_out_channels": 256,
+  "atrous_rates": [
+    6,
+    12,
+    18
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "classifier_dropout_prob": 0.1,
+  "conv_kernel_size": 3,
+  "expand_ratio": 4.0,
+  "hidden_act": "silu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_sizes": [
+    144,
+    192,
+    240
+  ],
+  "id2label": {
+    "0": "Barred Spiral",
+    "1": "Cigar Round Smooth",
+    "2": "Distributed",
+    "3": "Edge-on with Bulge",
+    "4": "Edge-on without Bulge",
+    "5": "In-between Round Smooth",
+    "6": "Merging",
+    "7": "Round Smooth",
+    "8": "Unbarred Loss Spiral",
+    "9": "Unbarred Tight Spiral"
+  },
+  "image_size": 256,
+  "initializer_range": 0.02,
+  "label2id": {
+    "Barred Spiral": "0",
+    "Cigar Round Smooth": "1",
+    "Distributed": "2",
+    "Edge-on with Bulge": "3",
+    "Edge-on without Bulge": "4",
+    "In-between Round Smooth": "5",
+    "Merging": "6",
+    "Round Smooth": "7",
+    "Unbarred Loss Spiral": "8",
+    "Unbarred Tight Spiral": "9"
+  },
+  "layer_norm_eps": 1e-05,
+  "mlp_ratio": 2.0,
+  "model_type": "mobilevit",
+  "neck_hidden_sizes": [
+    16,
+    32,
+    64,
+    96,
+    128,
+    160,
+    640
+  ],
+  "num_attention_heads": 4,
+  "num_channels": 3,
+  "output_stride": 32,
+  "patch_size": 2,
+  "qkv_bias": true,
+  "semantic_loss_ignore_index": 255,
+  "torch_dtype": "float32",
+  "transformers_version": "4.30.2"
+}

preprocessor_config.json

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+{
+  "crop_size": {
+    "height": 256,
+    "width": 256
+  },
+  "do_center_crop": true,
+  "do_flip_channel_order": true,
+  "do_flip_channels": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_processor_type": "MobileViTImageProcessor",
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 288
+  }
+}

tf_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b2924082e9a04113e443ed026adfd9a3b765ffcdf63354b94120c1e73e5d6e6e
+size 20255544