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--- |
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license: mit |
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base_model: nvidia/mit-b0 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: slm-segformer-080823 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# slm-segformer-080823 |
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This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0357 |
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- Validation Loss: 0.0383 |
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- Validation Mean Iou: 0.8453 |
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- Validation Mean Accuracy: 0.9366 |
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- Validation Overall Accuracy: 0.9869 |
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- Validation Per Category Iou: [0.98646921 0.70414361] |
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- Validation Per Category Accuracy: [0.99072207 0.88237991] |
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- Epoch: 9 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- 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} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Validation Mean Iou | Validation Mean Accuracy | Validation Overall Accuracy | Validation Per Category Iou | Validation Per Category Accuracy | Epoch | |
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|:----------:|:---------------:|:-------------------:|:------------------------:|:---------------------------:|:---------------------------:|:--------------------------------:|:-----:| |
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| 0.4798 | 0.1807 | 0.6747 | 0.7770 | 0.9674 | [0.96669254 0.38268484] | [0.98185208 0.57215982] | 0 | |
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| 0.1552 | 0.1046 | 0.7352 | 0.7991 | 0.9779 | [0.97745298 0.49298956] | [0.99154204 0.60674898] | 1 | |
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| 0.0981 | 0.1042 | 0.7744 | 0.9090 | 0.9779 | [0.97719564 0.5715319 ] | [0.98310851 0.8349177 ] | 2 | |
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| 0.0744 | 0.0978 | 0.7876 | 0.9431 | 0.9784 | [0.97773288 0.59755377] | [0.98113179 0.90515736] | 3 | |
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| 0.0611 | 0.0728 | 0.8224 | 0.9456 | 0.9836 | [0.98310869 0.66170563] | [0.98654807 0.90455283] | 4 | |
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| 0.0513 | 0.0531 | 0.8330 | 0.9282 | 0.9856 | [0.98518512 0.68084932] | [0.99000668 0.86647783] | 5 | |
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| 0.0469 | 0.0514 | 0.8326 | 0.9460 | 0.9850 | [0.98451475 0.68075519] | [0.9879771 0.90405278] | 6 | |
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| 0.0413 | 0.0406 | 0.8452 | 0.9360 | 0.9869 | [0.9864742 0.70392259] | [0.99077125 0.88115845] | 7 | |
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| 0.0385 | 0.0412 | 0.8495 | 0.9309 | 0.9875 | [0.98715291 0.71182272] | [0.99186047 0.86989475] | 8 | |
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| 0.0357 | 0.0383 | 0.8453 | 0.9366 | 0.9869 | [0.98646921 0.70414361] | [0.99072207 0.88237991] | 9 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- TensorFlow 2.12.0 |
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- Tokenizers 0.13.3 |
