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--- |
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license: other |
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base_model: nvidia/segformer-b0-finetuned-ade-512-512 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: Segformer-MRIseg_model_Mar24 |
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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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# Segformer-MRIseg_model_Mar24 |
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This model is a fine-tuned version of [nvidia/segformer-b0-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0037 |
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- Validation Loss: 0.0081 |
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- Epoch: 59 |
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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': 0.001, '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 | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 0.5861 | 0.0929 | 0 | |
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| 0.0953 | 0.0606 | 1 | |
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| 0.0509 | 0.0350 | 2 | |
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| 0.0308 | 0.0231 | 3 | |
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| 0.0253 | 0.0219 | 4 | |
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| 0.0202 | 0.0179 | 5 | |
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| 0.0162 | 0.0184 | 6 | |
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| 0.0152 | 0.0188 | 7 | |
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| 0.0135 | 0.0157 | 8 | |
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| 0.0119 | 0.0170 | 9 | |
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| 0.0110 | 0.0150 | 10 | |
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| 0.0102 | 0.0157 | 11 | |
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| 0.0097 | 0.0137 | 12 | |
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| 0.0095 | 0.0141 | 13 | |
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| 0.0087 | 0.0118 | 14 | |
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| 0.0079 | 0.0116 | 15 | |
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| 0.0075 | 0.0119 | 16 | |
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| 0.0072 | 0.0109 | 17 | |
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| 0.0069 | 0.0118 | 18 | |
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| 0.0068 | 0.0104 | 19 | |
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| 0.0065 | 0.0108 | 20 | |
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| 0.0064 | 0.0124 | 21 | |
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| 0.0062 | 0.0095 | 22 | |
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| 0.0058 | 0.0111 | 23 | |
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| 0.0058 | 0.0094 | 24 | |
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| 0.0056 | 0.0111 | 25 | |
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| 0.0055 | 0.0125 | 26 | |
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| 0.0057 | 0.0104 | 27 | |
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| 0.0053 | 0.0096 | 28 | |
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| 0.0051 | 0.0105 | 29 | |
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| 0.0050 | 0.0103 | 30 | |
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| 0.0048 | 0.0091 | 31 | |
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| 0.0047 | 0.0097 | 32 | |
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| 0.0044 | 0.0094 | 33 | |
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| 0.0045 | 0.0092 | 34 | |
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| 0.0045 | 0.0093 | 35 | |
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| 0.0047 | 0.0088 | 36 | |
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| 0.0048 | 0.0089 | 37 | |
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| 0.0045 | 0.0108 | 38 | |
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| 0.0043 | 0.0088 | 39 | |
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| 0.0043 | 0.0090 | 40 | |
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| 0.0044 | 0.0106 | 41 | |
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| 0.0053 | 0.0100 | 42 | |
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| 0.0051 | 0.0102 | 43 | |
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| 0.0044 | 0.0097 | 44 | |
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| 0.0039 | 0.0088 | 45 | |
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| 0.0040 | 0.0097 | 46 | |
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| 0.0040 | 0.0089 | 47 | |
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| 0.0037 | 0.0095 | 48 | |
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| 0.0034 | 0.0085 | 49 | |
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| 0.0041 | 0.0082 | 50 | |
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| 0.0054 | 0.0098 | 51 | |
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| 0.0053 | 0.0085 | 52 | |
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| 0.0044 | 0.0086 | 53 | |
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| 0.0040 | 0.0082 | 54 | |
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| 0.0038 | 0.0082 | 55 | |
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| 0.0035 | 0.0092 | 56 | |
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| 0.0034 | 0.0090 | 57 | |
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| 0.0035 | 0.0079 | 58 | |
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| 0.0037 | 0.0081 | 59 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- TensorFlow 2.15.0 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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