End of training

README.md

@@ -1,199 +1,92 @@
----
-library_name: transformers
-tags: []
----
-
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
-
-## Model Details
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
-
-## Training Details
-
-### Training Data
-
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-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).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]
+---
+library_name: transformers
+license: other
+base_model: nvidia/mit-b3
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: segformer-b0-finetuned-morphpadver1-hgo-coord-v3_1
+  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-b0-finetuned-morphpadver1-hgo-coord-v3_1
+
+This model is a fine-tuned version of [nvidia/mit-b3](https://huggingface.co/nvidia/mit-b3) on the NICOPOI-9/morphpad_coord_hgo_512_4class_v2 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0117
+- Mean Iou: 0.9981
+- Mean Accuracy: 0.9990
+- Overall Accuracy: 0.9990
+- Accuracy 0-0: 0.9995
+- Accuracy 0-90: 0.9985
+- Accuracy 90-0: 0.9988
+- Accuracy 90-90: 0.9993
+- Iou 0-0: 0.9991
+- Iou 0-90: 0.9979
+- Iou 90-0: 0.9976
+- Iou 90-90: 0.9978
+
+## 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: 1
+- eval_batch_size: 1
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 60
+
+### Training results
+
+| Training Loss | Epoch   | Step  | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy 0-0 | Accuracy 0-90 | Accuracy 90-0 | Accuracy 90-90 | Iou 0-0 | Iou 0-90 | Iou 90-0 | Iou 90-90 |
+|:-------------:|:-------:|:-----:|:---------------:|:--------:|:-------------:|:----------------:|:------------:|:-------------:|:-------------:|:--------------:|:-------:|:--------:|:--------:|:---------:|
+| 0.903         | 2.6525  | 4000  | 0.8952          | 0.3916   | 0.5570        | 0.5567           | 0.5335       | 0.6125        | 0.4890        | 0.5929         | 0.4534  | 0.3418   | 0.3411   | 0.4299    |
+| 0.6373        | 5.3050  | 8000  | 0.5078          | 0.6237   | 0.7643        | 0.7643           | 0.7676       | 0.8339        | 0.6741        | 0.7817         | 0.6758  | 0.5472   | 0.6022   | 0.6698    |
+| 0.2851        | 7.9576  | 12000 | 0.2955          | 0.7612   | 0.8642        | 0.8642           | 0.8669       | 0.8687        | 0.8339        | 0.8874         | 0.7959  | 0.7358   | 0.7500   | 0.7631    |
+| 0.2309        | 10.6101 | 16000 | 0.1305          | 0.9184   | 0.9574        | 0.9574           | 0.9575       | 0.9381        | 0.9648        | 0.9692         | 0.9333  | 0.9074   | 0.8991   | 0.9337    |
+| 0.0907        | 13.2626 | 20000 | 0.1249          | 0.9267   | 0.9620        | 0.9620           | 0.9636       | 0.9541        | 0.9594        | 0.9708         | 0.9379  | 0.9205   | 0.9169   | 0.9316    |
+| 0.3051        | 15.9151 | 24000 | 0.0529          | 0.9675   | 0.9835        | 0.9835           | 0.9842       | 0.9805        | 0.9839        | 0.9854         | 0.9712  | 0.9636   | 0.9626   | 0.9728    |
+| 0.0659        | 18.5676 | 28000 | 0.0630          | 0.9670   | 0.9832        | 0.9833           | 0.9852       | 0.9747        | 0.9885        | 0.9846         | 0.9719  | 0.9642   | 0.9633   | 0.9687    |
+| 0.0474        | 21.2202 | 32000 | 0.0454          | 0.9768   | 0.9882        | 0.9883           | 0.9910       | 0.9856        | 0.9865        | 0.9899         | 0.9783  | 0.9737   | 0.9747   | 0.9805    |
+| 0.0449        | 23.8727 | 36000 | 0.0468          | 0.9795   | 0.9896        | 0.9896           | 0.9900       | 0.9812        | 0.9900        | 0.9973         | 0.9828  | 0.9743   | 0.9783   | 0.9824    |
+| 0.0552        | 26.5252 | 40000 | 0.0266          | 0.9884   | 0.9942        | 0.9942           | 0.9949       | 0.9917        | 0.9947        | 0.9953         | 0.9888  | 0.9865   | 0.9866   | 0.9916    |
+| 0.0541        | 29.1777 | 44000 | 0.0290          | 0.9908   | 0.9954        | 0.9954           | 0.9951       | 0.9951        | 0.9967        | 0.9946         | 0.9921  | 0.9897   | 0.9905   | 0.9909    |
+| 0.0082        | 31.8302 | 48000 | 0.0421          | 0.9891   | 0.9945        | 0.9945           | 0.9940       | 0.9924        | 0.9951        | 0.9966         | 0.9908  | 0.9869   | 0.9884   | 0.9904    |
+| 0.0061        | 34.4828 | 52000 | 0.0345          | 0.9923   | 0.9961        | 0.9961           | 0.9971       | 0.9941        | 0.9966        | 0.9966         | 0.9939  | 0.9912   | 0.9916   | 0.9922    |
+| 0.0053        | 37.1353 | 56000 | 0.0256          | 0.9941   | 0.9970        | 0.9970           | 0.9976       | 0.9972        | 0.9966        | 0.9968         | 0.9957  | 0.9928   | 0.9929   | 0.9949    |
+| 0.0045        | 39.7878 | 60000 | 0.0256          | 0.9937   | 0.9968        | 0.9968           | 0.9978       | 0.9959        | 0.9959        | 0.9978         | 0.9937  | 0.9927   | 0.9926   | 0.9957    |
+| 0.0046        | 42.4403 | 64000 | 0.0171          | 0.9964   | 0.9982        | 0.9982           | 0.9983       | 0.9976        | 0.9987        | 0.9981         | 0.9972  | 0.9958   | 0.9955   | 0.9969    |
+| 0.0032        | 45.0928 | 68000 | 0.0293          | 0.9957   | 0.9979        | 0.9979           | 0.9983       | 0.9969        | 0.9975        | 0.9988         | 0.9966  | 0.9950   | 0.9950   | 0.9964    |
+| 0.003         | 47.7454 | 72000 | 0.0251          | 0.9964   | 0.9982        | 0.9982           | 0.9984       | 0.9973        | 0.9984        | 0.9987         | 0.9973  | 0.9952   | 0.9965   | 0.9966    |
+| 0.0035        | 50.3979 | 76000 | 0.0245          | 0.9973   | 0.9986        | 0.9986           | 0.9993       | 0.9982        | 0.9983        | 0.9987         | 0.9982  | 0.9969   | 0.9963   | 0.9977    |
+| 0.0025        | 53.0504 | 80000 | 0.0222          | 0.9972   | 0.9986        | 0.9986           | 0.9990       | 0.9980        | 0.9987        | 0.9986         | 0.9985  | 0.9965   | 0.9970   | 0.9968    |
+| 0.0023        | 55.7029 | 84000 | 0.0104          | 0.9982   | 0.9991        | 0.9991           | 0.9994       | 0.9989        | 0.9987        | 0.9993         | 0.9988  | 0.9980   | 0.9975   | 0.9983    |
+| 0.0022        | 58.3554 | 88000 | 0.0117          | 0.9981   | 0.9990        | 0.9990           | 0.9995       | 0.9985        | 0.9988        | 0.9993         | 0.9991  | 0.9979   | 0.9976   | 0.9978    |
+
+
+### Framework versions
+
+- Transformers 4.48.3
+- Pytorch 2.1.0
+- Datasets 3.2.0
+- Tokenizers 0.21.0

config.json

@@ -0,0 +1,82 @@
+{
+  "_name_or_path": "nvidia/mit-b3",
+  "architectures": [
+    "SegformerForSemanticSegmentation"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "classifier_dropout_prob": 0.1,
+  "decoder_hidden_size": 768,
+  "depths": [
+    3,
+    4,
+    18,
+    3
+  ],
+  "downsampling_rates": [
+    1,
+    4,
+    8,
+    16
+  ],
+  "drop_path_rate": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_sizes": [
+    64,
+    128,
+    320,
+    512
+  ],
+  "id2label": {
+    "0": "0-0",
+    "1": "0-90",
+    "2": "90-0",
+    "3": "90-90"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "0-0": 0,
+    "0-90": 1,
+    "90-0": 2,
+    "90-90": 3
+  },
+  "layer_norm_eps": 1e-06,
+  "mlp_ratios": [
+    4,
+    4,
+    4,
+    4
+  ],
+  "model_type": "segformer",
+  "num_attention_heads": [
+    1,
+    2,
+    5,
+    8
+  ],
+  "num_channels": 3,
+  "num_encoder_blocks": 4,
+  "patch_sizes": [
+    7,
+    3,
+    3,
+    3
+  ],
+  "reshape_last_stage": true,
+  "semantic_loss_ignore_index": 255,
+  "sr_ratios": [
+    8,
+    4,
+    2,
+    1
+  ],
+  "strides": [
+    4,
+    2,
+    2,
+    2
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.48.3"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d263f2677d85222c4d8a543cdcae0350cce2da771963730d8fa68a931939f9e7
+size 188985928

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c384bdc5a77246365368e355470ae86f16dfd1a5d326e80fc500da37d42f5f82
+size 5432