Model save

README.md

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+---
+license: other
+base_model: nvidia/mit-b0
+tags:
+- generated_from_trainer
+model-index:
+- name: baseline_plantorgans_model
+  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. -->
+
+# baseline_plantorgans_model
+
+This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5639
+- Mean Iou: 0.1095
+- Mean Accuracy: 0.1373
+- Overall Accuracy: 0.1858
+- Accuracy Void: nan
+- Accuracy Fruit: 0.5208
+- Accuracy Leaf: 0.0197
+- Accuracy Flower: 0.0
+- Accuracy Stem: 0.0087
+- Iou Void: 0.0
+- Iou Fruit: 0.5192
+- Iou Leaf: 0.0197
+- Iou Flower: 0.0
+- Iou Stem: 0.0087
+
+## 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 3.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Void | Accuracy Fruit | Accuracy Leaf | Accuracy Flower | Accuracy Stem | Iou Void | Iou Fruit | Iou Leaf | Iou Flower | Iou Stem |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------:|:--------------:|:-------------:|:---------------:|:-------------:|:--------:|:---------:|:--------:|:----------:|:--------:|
+| 0.8673        | 1.0   | 719  | 0.4827          | 0.1301   | 0.1639        | 0.2227           | nan           | 0.6188         | 0.0271        | 0.0             | 0.0098        | 0.0      | 0.6135    | 0.0271   | 0.0        | 0.0098   |
+| 0.4457        | 2.0   | 1438 | 0.5555          | 0.1130   | 0.1416        | 0.1927           | nan           | 0.5224         | 0.0305        | 0.0             | 0.0135        | 0.0      | 0.5209    | 0.0305   | 0.0        | 0.0135   |
+| 0.3272        | 3.0   | 2157 | 0.5639          | 0.1095   | 0.1373        | 0.1858           | nan           | 0.5208         | 0.0197        | 0.0             | 0.0087        | 0.0      | 0.5192    | 0.0197   | 0.0        | 0.0087   |
+
+
+### Framework versions
+
+- Transformers 4.38.0.dev0
+- Pytorch 2.1.2+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0