End of training

README.md

@@ -1,199 +1,81 @@
 ---
-library_name: transformers
-tags: []
+license: other
+base_model: nvidia/mit-b0
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: segformer-b0-finetuned-segments-sidewalk-test
+  results: []
 ---
 
-# Model Card for Model ID
+<!-- 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. -->
 
-<!-- Provide a quick summary of what the model is/does. -->
+# segformer-b0-finetuned-segments-sidewalk-test
 
+This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the segments/sidewalk-semantic dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1620
+- Mean Iou: 0.4717
+- Mean Accuracy: 0.9435
+- Overall Accuracy: 0.9435
+- Accuracy Other: nan
+- Accuracy Flat-sidewalk: 0.9435
+- Iou Other: 0.0
+- Iou Flat-sidewalk: 0.9435
 
+## Model description
 
-## Model Details
+More information needed
 
-### Model Description
+## Intended uses & limitations
 
-<!-- Provide a longer summary of what this model is. -->
+More information needed
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+## Training and evaluation data
 
-- **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]
+More information needed
 
-### Model Sources [optional]
+## Training procedure
 
-<!-- Provide the basic links for the model. -->
+### Training hyperparameters
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+The following hyperparameters were used during training:
+- learning_rate: 6e-05
+- train_batch_size: 5
+- eval_batch_size: 5
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
 
-## Uses
+### Training results
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Other | Accuracy Flat-sidewalk | Iou Other | Iou Flat-sidewalk |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:--------------:|:----------------------:|:---------:|:-----------------:|
+| 0.0426        | 0.125 | 20   | 0.1662          | 0.4707   | 0.9414        | 0.9414           | nan            | 0.9414                 | 0.0       | 0.9414            |
+| 0.0301        | 0.25  | 40   | 0.1757          | 0.4761   | 0.9522        | 0.9522           | nan            | 0.9522                 | 0.0       | 0.9522            |
+| 0.0307        | 0.375 | 60   | 0.1795          | 0.4676   | 0.9353        | 0.9353           | nan            | 0.9353                 | 0.0       | 0.9353            |
+| 0.0451        | 0.5   | 80   | 0.1655          | 0.4730   | 0.9460        | 0.9460           | nan            | 0.9460                 | 0.0       | 0.9460            |
+| 0.041         | 0.625 | 100  | 0.1745          | 0.4726   | 0.9452        | 0.9452           | nan            | 0.9452                 | 0.0       | 0.9452            |
+| 0.0406        | 0.75  | 120  | 0.1629          | 0.4769   | 0.9539        | 0.9539           | nan            | 0.9539                 | 0.0       | 0.9539            |
+| 0.0798        | 0.875 | 140  | 0.1594          | 0.4686   | 0.9372        | 0.9372           | nan            | 0.9372                 | 0.0       | 0.9372            |
+| 0.0349        | 1.0   | 160  | 0.1582          | 0.4718   | 0.9436        | 0.9436           | nan            | 0.9436                 | 0.0       | 0.9436            |
+| 0.0566        | 1.125 | 180  | 0.1785          | 0.4654   | 0.9307        | 0.9307           | nan            | 0.9307                 | 0.0       | 0.9307            |
+| 0.0283        | 1.25  | 200  | 0.1637          | 0.4735   | 0.9470        | 0.9470           | nan            | 0.9470                 | 0.0       | 0.9470            |
+| 0.0262        | 1.375 | 220  | 0.1740          | 0.4760   | 0.9519        | 0.9519           | nan            | 0.9519                 | 0.0       | 0.9519            |
+| 0.0335        | 1.5   | 240  | 0.1640          | 0.4733   | 0.9465        | 0.9465           | nan            | 0.9465                 | 0.0       | 0.9465            |
+| 0.0365        | 1.625 | 260  | 0.1631          | 0.4737   | 0.9474        | 0.9474           | nan            | 0.9474                 | 0.0       | 0.9474            |
+| 0.0781        | 1.75  | 280  | 0.1653          | 0.4733   | 0.9466        | 0.9466           | nan            | 0.9466                 | 0.0       | 0.9466            |
+| 0.0846        | 1.875 | 300  | 0.1671          | 0.4724   | 0.9449        | 0.9449           | nan            | 0.9449                 | 0.0       | 0.9449            |
+| 0.0301        | 2.0   | 320  | 0.1620          | 0.4717   | 0.9435        | 0.9435           | nan            | 0.9435                 | 0.0       | 0.9435            |
 
-### Direct Use
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+### Framework versions
 
-[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]
+- Transformers 4.41.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

@@ -0,0 +1,78 @@
+{
+  "_name_or_path": "nvidia/mit-b0",
+  "architectures": [
+    "SegformerForSemanticSegmentation"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "classifier_dropout_prob": 0.1,
+  "decoder_hidden_size": 256,
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsampling_rates": [
+    1,
+    4,
+    8,
+    16
+  ],
+  "drop_path_rate": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_sizes": [
+    32,
+    64,
+    160,
+    256
+  ],
+  "id2label": {
+    "0": "other",
+    "1": "flat-sidewalk"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "flat-sidewalk": 1,
+    "other": 0
+  },
+  "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": "4.41.1"
+}

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