update model card README.md

README.md

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+---
+license: other
+base_model: nvidia/mit-b0
+tags:
+- image-segmentation
+- vision
+- generated_from_trainer
+model-index:
+- name: segformer-finetuned-ihc
+  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. -->
+
+# segformer-finetuned-ihc
+
+This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the Isaacks/ihc_slide_tissue dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 0.0326
+- eval_mean_iou: 0.0
+- eval_mean_accuracy: nan
+- eval_overall_accuracy: nan
+- eval_accuracy_background: nan
+- eval_accuracy_tissue: nan
+- eval_iou_background: 0.0
+- eval_iou_tissue: 0.0
+- eval_runtime: 19.1281
+- eval_samples_per_second: 0.784
+- eval_steps_per_second: 0.105
+- epoch: 9.15
+- step: 183
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 1337
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: polynomial
+- training_steps: 10000
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.2
+- Tokenizers 0.13.3