update model card README.md

README.md

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+---
+license: other
+tags:
+- generated_from_trainer
+model-index:
+- name: segment_50ep
+  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. -->
+
+# segment_50ep
+
+This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the None dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 0.0867
+- eval_mean_iou: 0.8941
+- eval_mean_accuracy: 0.9459
+- eval_overall_accuracy: 0.9728
+- eval_per_category_iou: [0.8914159628180123, 0.9397057910334902, 0.784713695838044, 0.9606094621573129]
+- eval_per_category_accuracy: [0.9685998627316403, 0.9696767617484154, 0.8661740631737143, 0.9789942690602516]
+- eval_runtime: 40.9902
+- eval_samples_per_second: 0.976
+- eval_steps_per_second: 0.244
+- epoch: 36.82
+- step: 3240
+
+## 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: 50
+
+### Framework versions
+
+- Transformers 4.26.1
+- Pytorch 1.13.0
+- Datasets 2.10.1
+- Tokenizers 0.13.2