Training in progress epoch 0

README.md

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+---
+license: other
+base_model: nvidia/mit-b1
+tags:
+- generated_from_keras_callback
+model-index:
+- name: Lit4pCol4b/mit-b1_segformer_ADE20k_RGB_IS_v1
+  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. -->
+
+# Lit4pCol4b/mit-b1_segformer_ADE20k_RGB_IS_v1
+
+This model is a fine-tuned version of [nvidia/mit-b1](https://huggingface.co/nvidia/mit-b1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Train Loss: nan
+- Validation Loss: nan
+- Validation Mean Iou: 0.0425
+- Validation Mean Accuracy: 1.0
+- Validation Overall Accuracy: 1.0
+- Validation Accuracy Unlabeled: 1.0
+- Validation Accuracy Objeto Interes: nan
+- Validation Accuracy Agua: nan
+- Validation Iou Unlabeled: 0.0425
+- Validation Iou Objeto Interes: nan
+- Validation Iou Agua: nan
+- 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': 'Adam', 'weight_decay': None, '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': 6e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
+- training_precision: float32
+
+### Training results
+
+| Train Loss | Validation Loss | Validation Mean Iou | Validation Mean Accuracy | Validation Overall Accuracy | Validation Accuracy Unlabeled | Validation Accuracy Objeto Interes | Validation Accuracy Agua | Validation Iou Unlabeled | Validation Iou Objeto Interes | Validation Iou Agua | Epoch |
+|:----------:|:---------------:|:-------------------:|:------------------------:|:---------------------------:|:-----------------------------:|:----------------------------------:|:------------------------:|:------------------------:|:-----------------------------:|:-------------------:|:-----:|
+| nan        | nan             | 0.0425              | 1.0                      | 1.0                         | 1.0                           | nan                                | nan                      | 0.0425                   | nan                           | nan                 | 0     |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- TensorFlow 2.15.0
+- Datasets 2.16.1
+- Tokenizers 0.15.0

config.json

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+{
+  "_name_or_path": "nvidia/mit-b1",
+  "architectures": [
+    "SegformerForSemanticSegmentation"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "classifier_dropout_prob": 0.1,
+  "decoder_hidden_size": 256,
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsampling_rates": [
+    1,
+    4,
+    8,
+    16
+  ],
+  "drop_path_rate": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_sizes": [
+    64,
+    128,
+    320,
+    512
+  ],
+  "id2label": {
+    "0": "unlabeled",
+    "1": "objeto_interes",
+    "2": "agua"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "agua": 2,
+    "objeto_interes": 1,
+    "unlabeled": 0
+  },
+  "layer_norm_eps": 1e-06,
+  "mlp_ratios": [
+    4,
+    4,
+    4,
+    4
+  ],
+  "model_type": "segformer",
+  "num_attention_heads": [
+    1,
+    2,
+    5,
+    8
+  ],
+  "num_channels": 3,
+  "num_encoder_blocks": 4,
+  "patch_sizes": [
+    7,
+    3,
+    3,
+    3
+  ],
+  "reshape_last_stage": true,
+  "semantic_loss_ignore_index": 255,
+  "sr_ratios": [
+    8,
+    4,
+    2,
+    1
+  ],
+  "strides": [
+    4,
+    2,
+    2,
+    2
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.35.2"
+}

preprocessor_config.json

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+{
+  "do_normalize": true,
+  "do_reduce_labels": false,
+  "do_rescale": false,
+  "do_resize": false,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "SegformerImageProcessor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 736,
+    "width": 736
+  }
+}

tf_model.h5

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+oid sha256:aa12aba4742e7e3cede1fc187f04e30b2864dc846d87b5b6281334d5336702d4
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