End of training
Browse files- README.md +87 -196
- config.json +80 -0
- model.safetensors +3 -0
- runs/Jul22_14-02-29_lrz-hgx-a100-003/events.out.tfevents.1721649775.lrz-hgx-a100-003.3340635.0 +3 -0
- training_args.bin +3 -0
README.md
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##
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###
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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[More Information Needed]
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#### Factors
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[More Information Needed]
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#### Metrics
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[More Information Needed]
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### Results
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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## More Information [optional]
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## Model Card Authors [optional]
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## Model Card Contact
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[More Information Needed]
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---
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license: other
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base_model: nvidia/mit-b5
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tags:
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- vision
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- image-segmentation
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- generated_from_trainer
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model-index:
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- name: SegFormer_mit-b5_Clean-Set3-Grayscale_Augmented_Medium_16
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# SegFormer_mit-b5_Clean-Set3-Grayscale_Augmented_Medium_16
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This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on the Hasano20/Clean-Set3 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0121
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- Mean Iou: 0.9823
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- Mean Accuracy: 0.9920
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- Overall Accuracy: 0.9954
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- Accuracy Background: 0.9974
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- Accuracy Melt: 0.9828
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- Accuracy Substrate: 0.9958
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- Iou Background: 0.9943
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- Iou Melt: 0.9594
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- Iou Substrate: 0.9932
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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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- learning_rate: 0.0002
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 100
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- num_epochs: 20
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Melt | Accuracy Substrate | Iou Background | Iou Melt | Iou Substrate |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-------------:|:------------------:|:--------------:|:--------:|:-------------:|
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| 0.1196 | 0.7937 | 50 | 0.1076 | 0.8582 | 0.8965 | 0.9626 | 0.9674 | 0.7265 | 0.9955 | 0.9625 | 0.6696 | 0.9424 |
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| 0.2728 | 1.5873 | 100 | 0.0878 | 0.8762 | 0.9239 | 0.9665 | 0.9622 | 0.8161 | 0.9935 | 0.9611 | 0.7150 | 0.9525 |
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| 0.2668 | 2.3810 | 150 | 0.1131 | 0.8710 | 0.9238 | 0.9639 | 0.9971 | 0.8140 | 0.9602 | 0.9620 | 0.7076 | 0.9432 |
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| 0.0337 | 3.1746 | 200 | 0.0610 | 0.9173 | 0.9613 | 0.9778 | 0.9709 | 0.9208 | 0.9923 | 0.9685 | 0.8110 | 0.9723 |
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| 0.0443 | 3.9683 | 250 | 0.0295 | 0.9527 | 0.9665 | 0.9885 | 0.9924 | 0.9095 | 0.9977 | 0.9902 | 0.8867 | 0.9812 |
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| 0.0283 | 4.7619 | 300 | 0.0220 | 0.9652 | 0.9781 | 0.9915 | 0.9965 | 0.9429 | 0.9950 | 0.9910 | 0.9175 | 0.9871 |
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| 0.0166 | 5.5556 | 350 | 0.0193 | 0.9683 | 0.9837 | 0.9922 | 0.9972 | 0.9609 | 0.9929 | 0.9925 | 0.9249 | 0.9876 |
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| 0.0218 | 6.3492 | 400 | 0.0190 | 0.9691 | 0.9871 | 0.9922 | 0.9975 | 0.9730 | 0.9909 | 0.9919 | 0.9277 | 0.9879 |
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| 0.0178 | 7.1429 | 450 | 0.0157 | 0.9752 | 0.9853 | 0.9938 | 0.9981 | 0.9626 | 0.9951 | 0.9925 | 0.9424 | 0.9909 |
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| 0.0165 | 7.9365 | 500 | 0.0151 | 0.9771 | 0.9878 | 0.9941 | 0.9966 | 0.9711 | 0.9957 | 0.9931 | 0.9470 | 0.9911 |
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| 0.0136 | 8.7302 | 550 | 0.0137 | 0.9785 | 0.9902 | 0.9945 | 0.9955 | 0.9792 | 0.9959 | 0.9930 | 0.9508 | 0.9918 |
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| 0.0127 | 9.5238 | 600 | 0.0128 | 0.9798 | 0.9896 | 0.9948 | 0.9977 | 0.9758 | 0.9955 | 0.9937 | 0.9536 | 0.9923 |
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| 0.0117 | 10.3175 | 650 | 0.0123 | 0.9809 | 0.9895 | 0.9951 | 0.9974 | 0.9747 | 0.9964 | 0.9939 | 0.9561 | 0.9927 |
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| 0.011 | 11.1111 | 700 | 0.0125 | 0.9805 | 0.9923 | 0.9950 | 0.9974 | 0.9848 | 0.9946 | 0.9938 | 0.9552 | 0.9925 |
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| 0.0108 | 11.9048 | 750 | 0.0123 | 0.9809 | 0.9915 | 0.9951 | 0.9975 | 0.9818 | 0.9952 | 0.9940 | 0.9561 | 0.9926 |
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| 0.0135 | 12.6984 | 800 | 0.0126 | 0.9808 | 0.9920 | 0.9950 | 0.9979 | 0.9834 | 0.9946 | 0.9941 | 0.9558 | 0.9924 |
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| 0.0089 | 13.4921 | 850 | 0.0123 | 0.9814 | 0.9923 | 0.9952 | 0.9968 | 0.9844 | 0.9957 | 0.9940 | 0.9574 | 0.9929 |
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| 0.0077 | 14.2857 | 900 | 0.0119 | 0.9819 | 0.9911 | 0.9953 | 0.9976 | 0.9797 | 0.9959 | 0.9942 | 0.9586 | 0.9930 |
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| 0.0069 | 15.0794 | 950 | 0.0122 | 0.9822 | 0.9914 | 0.9954 | 0.9973 | 0.9807 | 0.9961 | 0.9943 | 0.9591 | 0.9931 |
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| 0.0069 | 15.8730 | 1000 | 0.0120 | 0.9822 | 0.9920 | 0.9954 | 0.9975 | 0.9828 | 0.9957 | 0.9944 | 0.9592 | 0.9931 |
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| 0.0089 | 16.6667 | 1050 | 0.0120 | 0.9824 | 0.9914 | 0.9955 | 0.9976 | 0.9807 | 0.9961 | 0.9943 | 0.9595 | 0.9932 |
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| 0.0072 | 17.4603 | 1100 | 0.0121 | 0.9823 | 0.9920 | 0.9954 | 0.9974 | 0.9828 | 0.9958 | 0.9943 | 0.9594 | 0.9932 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.0.1+cu117
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- Datasets 2.19.2
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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/mit-b5",
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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": 768,
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"depths": [
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3,
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40,
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3
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],
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"downsampling_rates": [
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1,
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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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64,
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128,
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320,
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512
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],
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"id2label": {
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"0": "background",
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"1": "melt",
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"2": "substrate"
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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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"background": 0,
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"melt": 1,
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"substrate": 2
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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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],
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"model_type": "segformer",
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"num_attention_heads": [
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1,
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2,
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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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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,
|
68 |
+
4,
|
69 |
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2,
|
70 |
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1
|
71 |
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],
|
72 |
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"strides": [
|
73 |
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|
74 |
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|
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|
76 |
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|
77 |
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],
|
78 |
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"torch_dtype": "float32",
|
79 |
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"transformers_version": "4.41.2"
|
80 |
+
}
|
model.safetensors
ADDED
@@ -0,0 +1,3 @@
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|
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|
|
1 |
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version https://git-lfs.github.com/spec/v1
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2 |
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oid sha256:e280c6d188a95ef47f299bd8be2ffb14fa2c9ed18741b9209638ae447df3c39f
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3 |
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size 338531516
|
runs/Jul22_14-02-29_lrz-hgx-a100-003/events.out.tfevents.1721649775.lrz-hgx-a100-003.3340635.0
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
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version https://git-lfs.github.com/spec/v1
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2 |
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oid sha256:c85ed81c4e717126ab1a96d346a9dbf449ef7c83574f45ee68d1f4bc74143044
|
3 |
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size 255068
|
training_args.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
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2 |
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oid sha256:6b8dabf84b011e14732577bd3d1d6f4257feec9bea754a9b1dae9939660850a8
|
3 |
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size 4987
|