bhaskarSingha
commited on
Commit
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Parent(s):
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Training in progress epoch 0
Browse files- README.md +63 -0
- config.json +80 -0
- preprocessor_config.json +39 -0
- tf_model.h5 +3 -0
README.md
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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: bhaskarSingha/segformer-finetuned-paddyV1
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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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# bhaskarSingha/segformer-finetuned-paddyV1
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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: nan
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- Validation Loss: nan
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- Validation Mean Iou: 0.0004
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- Validation Mean Accuracy: 0.5
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- Validation Overall Accuracy: 0.1499
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- Validation Accuracy Healthy: 1.0
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- Validation Accuracy Brownspot: 0.0
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- Validation Accuracy Leafblast: nan
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- Validation Iou Healthy: 0.0009
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- Validation Iou Brownspot: 0.0
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- Validation Iou Leafblast: nan
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- Epoch: 0
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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': {'module': 'keras.optimizers.schedules', 'class_name': 'CosineDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 1000, 'alpha': 0.0, 'name': 'CosineDecay', 'warmup_target': 5e-05, 'warmup_steps': 100}, 'registered_name': None}, '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 Accuracy Healthy | Validation Accuracy Brownspot | Validation Accuracy Leafblast | Validation Iou Healthy | Validation Iou Brownspot | Validation Iou Leafblast | Epoch |
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|:----------:|:---------------:|:-------------------:|:------------------------:|:---------------------------:|:---------------------------:|:-----------------------------:|:-----------------------------:|:----------------------:|:------------------------:|:------------------------:|:-----:|
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| nan | nan | 0.0004 | 0.5 | 0.1499 | 1.0 | 0.0 | nan | 0.0009 | 0.0 | nan | 0 |
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### Framework versions
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- Transformers 4.40.2
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- TensorFlow 2.15.0
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- Datasets 2.15.0
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- Tokenizers 0.19.1
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config.json
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{
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"_name_or_path": "nvidia/segformer-b0-finetuned-ade-512-512",
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"architectures": [
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"SegformerForSemanticSegmentation"
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],
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"attention_probs_dropout_prob": 0.0,
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"classifier_dropout_prob": 0.1,
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"decoder_hidden_size": 256,
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"depths": [
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2,
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2,
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2,
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2
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],
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"downsampling_rates": [
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1,
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4,
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8,
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16
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],
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"drop_path_rate": 0.1,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.0,
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"hidden_sizes": [
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32,
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64,
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160,
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256
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],
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"id2label": {
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"1": "Healthy",
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"2": "Brownspot",
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"3": "LeafBlast"
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},
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"image_size": 224,
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"initializer_range": 0.02,
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"label2id": {
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"Brownspot": 2,
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"Healthy": 1,
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"LeafBlast": 3
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},
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"layer_norm_eps": 1e-06,
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"mlp_ratios": [
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4,
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4,
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4,
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4
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],
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"model_type": "segformer",
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"num_attention_heads": [
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1,
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5,
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8
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],
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"num_channels": 3,
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"num_encoder_blocks": 4,
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"patch_sizes": [
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7,
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3,
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3,
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3
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],
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"reshape_last_stage": true,
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"semantic_loss_ignore_index": 255,
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"sr_ratios": [
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8,
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4,
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2,
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1
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],
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"strides": [
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4,
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2,
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],
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"torch_dtype": "float32",
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"transformers_version": "4.40.2"
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}
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preprocessor_config.json
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{
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"_valid_processor_keys": [
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"images",
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"segmentation_maps",
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"do_resize",
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"size",
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"resample",
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"do_rescale",
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"rescale_factor",
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"do_normalize",
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"image_mean",
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"image_std",
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"do_reduce_labels",
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"return_tensors",
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"data_format",
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"input_data_format"
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],
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"do_normalize": true,
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"do_reduce_labels": true,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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0.485,
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0.456,
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0.406
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],
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"image_processor_type": "SegformerImageProcessor",
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"image_std": [
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0.229,
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0.224,
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0.225
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],
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"resample": 2,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"height": 512,
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"width": 512
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}
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}
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tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:2081ea5ce8f49d13186afdd097554b5e52ff004b855780c3916f64dcce304b18
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size 15134580
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