End of training

README.md

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+---
+library_name: transformers
+license: apple-amlr
+base_model: apple/deeplabv3-mobilevit-small
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: deeplabv3-mobilevit-small_corm
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# deeplabv3-mobilevit-small_corm
+
+This model is a fine-tuned version of [apple/deeplabv3-mobilevit-small](https://huggingface.co/apple/deeplabv3-mobilevit-small) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7777
+- Mean Iou: 0.4137
+- Mean Accuracy: 0.5038
+- Overall Accuracy: 0.7714
+- Accuracy Background: 0.9998
+- Accuracy Corm: 0.0748
+- Accuracy Damage: 0.4368
+- Iou Background: 0.7626
+- Iou Corm: 0.0734
+- Iou Damage: 0.4050
+
+## 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:
+- learning_rate: 6e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Corm | Accuracy Damage | Iou Background | Iou Corm | Iou Damage |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-------------:|:---------------:|:--------------:|:--------:|:----------:|
+| 1.0611        | 0.3077 | 20   | 1.0627          | 0.4251   | 0.6398        | 0.6594           | 0.6709              | 0.5632        | 0.6853          | 0.6508         | 0.2723   | 0.3522     |
+| 1.0077        | 0.6154 | 40   | 1.0227          | 0.5359   | 0.6715        | 0.8018           | 0.9058              | 0.4028        | 0.7060          | 0.8285         | 0.3049   | 0.4743     |
+| 1.0089        | 0.9231 | 60   | 0.9859          | 0.5131   | 0.6138        | 0.8167           | 0.9804              | 0.2104        | 0.6506          | 0.8345         | 0.1883   | 0.5167     |
+| 0.9397        | 1.2308 | 80   | 0.9637          | 0.4767   | 0.5831        | 0.8103           | 0.9867              | 0.0722        | 0.6904          | 0.8293         | 0.0701   | 0.5307     |
+| 0.9347        | 1.5385 | 100  | 0.9257          | 0.4544   | 0.5545        | 0.7991           | 0.9946              | 0.0517        | 0.6172          | 0.8103         | 0.0504   | 0.5024     |
+| 0.9007        | 1.8462 | 120  | 0.9054          | 0.4458   | 0.5428        | 0.7926           | 0.9968              | 0.0678        | 0.5637          | 0.8012         | 0.0658   | 0.4705     |
+| 0.8787        | 2.1538 | 140  | 0.8756          | 0.4195   | 0.5140        | 0.7780           | 0.9986              | 0.0506        | 0.4927          | 0.7790         | 0.0495   | 0.4301     |
+| 0.8757        | 2.4615 | 160  | 0.8501          | 0.4035   | 0.4967        | 0.7677           | 0.9994              | 0.0659        | 0.4247          | 0.7656         | 0.0645   | 0.3804     |
+| 0.841         | 2.7692 | 180  | 0.8339          | 0.4199   | 0.5148        | 0.7799           | 0.9987              | 0.0283        | 0.5174          | 0.7791         | 0.0279   | 0.4528     |
+| 0.8268        | 3.0769 | 200  | 0.8246          | 0.4358   | 0.5279        | 0.7844           | 0.9989              | 0.0809        | 0.5040          | 0.7826         | 0.0789   | 0.4460     |
+| 0.8306        | 3.3846 | 220  | 0.8095          | 0.4034   | 0.4968        | 0.7690           | 0.9995              | 0.0461        | 0.4448          | 0.7653         | 0.0455   | 0.3995     |
+| 0.826         | 3.6923 | 240  | 0.7928          | 0.4174   | 0.5078        | 0.7731           | 0.9997              | 0.0846        | 0.4391          | 0.7663         | 0.0826   | 0.4034     |
+| 0.7873        | 4.0    | 260  | 0.7915          | 0.4150   | 0.5046        | 0.7713           | 0.9996              | 0.0842        | 0.4299          | 0.7616         | 0.0824   | 0.4009     |
+| 0.8031        | 4.3077 | 280  | 0.7805          | 0.4022   | 0.4928        | 0.7648           | 0.9998              | 0.0826        | 0.3960          | 0.7557         | 0.0811   | 0.3699     |
+| 0.7881        | 4.6154 | 300  | 0.7791          | 0.4352   | 0.5265        | 0.7848           | 0.9995              | 0.0659        | 0.5142          | 0.7808         | 0.0645   | 0.4604     |
+| 0.7883        | 4.9231 | 320  | 0.7777          | 0.4137   | 0.5038        | 0.7714           | 0.9998              | 0.0748        | 0.4368          | 0.7626         | 0.0734   | 0.4050     |
+
+
+### Framework versions
+
+- Transformers 4.44.1
+- Pytorch 2.6.0+cpu
+- Datasets 2.21.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "apple/deeplabv3-mobilevit-small",
+  "architectures": [
+    "MobileViTForSemanticSegmentation"
+  ],
+  "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": "background",
+    "1": "corm",
+    "2": "damage"
+  },
+  "image_size": 512,
+  "initializer_range": 0.02,
+  "label2id": {
+    "background": 0,
+    "corm": 1,
+    "damage": 2
+  },
+  "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": 16,
+  "patch_size": 2,
+  "qkv_bias": true,
+  "semantic_loss_ignore_index": 255,
+  "torch_dtype": "float32",
+  "transformers_version": "4.44.1"
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ed7343b02e0ac4950adf1da77f825a694fbe3515aff827380506b6373718b77e
+size 25520068

preprocessor_config.json

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+{
+  "crop_size": {
+    "height": 512,
+    "width": 512
+  },
+  "do_center_crop": true,
+  "do_flip_channel_order": true,
+  "do_flip_channels": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_processor_type": "MobileViTFeatureExtractor",
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 544
+  }
+}

training_args.bin

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+size 5240