Hasano20
/

BEiT_beit-base-finetuned-ade-640-640_Clean-Set3_RGB

@@ -1,199 +1,105 @@
 ---
-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]

 ---
+base_model: beit-base-finetuned-ade-640-640
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: BEiT_beit-base-finetuned-ade-640-640_Clean-Set3_RGB
+  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. -->
+# BEiT_beit-base-finetuned-ade-640-640_Clean-Set3_RGB
+This model is a fine-tuned version of [beit-base-finetuned-ade-640-640](https://huggingface.co/beit-base-finetuned-ade-640-640) on the Hasano20/Clean-Set3 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0336
+- Mean Iou: 0.9671
+- Mean Accuracy: 0.9806
+- Overall Accuracy: 0.9926
+- Accuracy Background: 0.9956
+- Accuracy Melt: 0.9505
+- Accuracy Substrate: 0.9957
+- Iou Background: 0.9916
+- Iou Melt: 0.9208
+- Iou Substrate: 0.9888
+## 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: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 200
+- num_epochs: 50
+### Training results
+| Training Loss | Epoch   | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Melt | Accuracy Substrate | Iou Background | Iou Melt | Iou Substrate |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-------------:|:------------------:|:--------------:|:--------:|:-------------:|
+| 0.4042        | 0.9434  | 50   | 0.3272          | 0.8363   | 0.8672        | 0.9671           | 0.9931              | 0.6175        | 0.9911             | 0.9836         | 0.5790   | 0.9463        |
+| 0.1649        | 1.8868  | 100  | 0.0973          | 0.9371   | 0.9572        | 0.9867           | 0.9959              | 0.8833        | 0.9926             | 0.9881         | 0.8437   | 0.9795        |
+| 0.1439        | 2.8302  | 150  | 0.0724          | 0.9495   | 0.9800        | 0.9887           | 0.9946              | 0.9575        | 0.9879             | 0.9898         | 0.8770   | 0.9818        |
+| 0.1275        | 3.7736  | 200  | 0.0656          | 0.9443   | 0.9778        | 0.9877           | 0.9969              | 0.9515        | 0.9850             | 0.9903         | 0.8627   | 0.9799        |
+| 0.1522        | 4.7170  | 250  | 0.0585          | 0.9567   | 0.9737        | 0.9899           | 0.9971              | 0.9325        | 0.9915             | 0.9887         | 0.8976   | 0.9839        |
+| 0.1292        | 5.6604  | 300  | 0.0594          | 0.9502   | 0.9748        | 0.9877           | 0.9934              | 0.9418        | 0.9890             | 0.9857         | 0.8850   | 0.9801        |
+| 0.097         | 6.6038  | 350  | 0.0450          | 0.9634   | 0.9775        | 0.9912           | 0.9949              | 0.9432        | 0.9943             | 0.9883         | 0.9154   | 0.9866        |
+| 0.1125        | 7.5472  | 400  | 0.0451          | 0.9605   | 0.9757        | 0.9905           | 0.9953              | 0.9384        | 0.9934             | 0.9877         | 0.9080   | 0.9857        |
+| 0.102         | 8.4906  | 450  | 0.0518          | 0.9531   | 0.9798        | 0.9876           | 0.9921              | 0.9596        | 0.9876             | 0.9824         | 0.8960   | 0.9808        |
+| 0.0878        | 9.4340  | 500  | 0.0411          | 0.9639   | 0.9820        | 0.9911           | 0.9947              | 0.9592        | 0.9922             | 0.9885         | 0.9172   | 0.9859        |
+| 0.1198        | 10.3774 | 550  | 0.0679          | 0.9398   | 0.9655        | 0.9821           | 0.9873              | 0.9237        | 0.9855             | 0.9708         | 0.8768   | 0.9719        |
+| 0.055         | 11.3208 | 600  | 0.0521          | 0.9518   | 0.9791        | 0.9867           | 0.9846              | 0.9610        | 0.9917             | 0.9780         | 0.8966   | 0.9810        |
+| 0.086         | 12.2642 | 650  | 0.0402          | 0.9631   | 0.9791        | 0.9903           | 0.9920              | 0.9514        | 0.9940             | 0.9861         | 0.9185   | 0.9848        |
+| 0.058         | 13.2075 | 700  | 0.0455          | 0.9590   | 0.9768        | 0.9892           | 0.9908              | 0.9463        | 0.9934             | 0.9837         | 0.9096   | 0.9836        |
+| 0.0494        | 14.1509 | 750  | 0.0441          | 0.9588   | 0.9796        | 0.9895           | 0.9926              | 0.9547        | 0.9914             | 0.9842         | 0.9076   | 0.9846        |
+| 0.0599        | 15.0943 | 800  | 0.0401          | 0.9622   | 0.9787        | 0.9904           | 0.9925              | 0.9496        | 0.9939             | 0.9865         | 0.9149   | 0.9851        |
+| 0.0422        | 16.0377 | 850  | 0.0393          | 0.9619   | 0.9807        | 0.9906           | 0.9946              | 0.9556        | 0.9919             | 0.9880         | 0.9123   | 0.9853        |
+| 0.0454        | 16.9811 | 900  | 0.0429          | 0.9579   | 0.9742        | 0.9897           | 0.9918              | 0.9360        | 0.9948             | 0.9857         | 0.9033   | 0.9846        |
+| 0.0806        | 17.9245 | 950  | 0.0377          | 0.9640   | 0.9779        | 0.9915           | 0.9928              | 0.9445        | 0.9964             | 0.9892         | 0.9157   | 0.9869        |
+| 0.0677        | 18.8679 | 1000 | 0.0380          | 0.9602   | 0.9797        | 0.9910           | 0.9941              | 0.9513        | 0.9937             | 0.9882         | 0.9047   | 0.9877        |
+| 0.036         | 19.8113 | 1050 | 0.0388          | 0.9618   | 0.9799        | 0.9906           | 0.9942              | 0.9529        | 0.9925             | 0.9868         | 0.9127   | 0.9860        |
+| 0.0424        | 20.7547 | 1100 | 0.0375          | 0.9601   | 0.9753        | 0.9905           | 0.9934              | 0.9376        | 0.9949             | 0.9868         | 0.9071   | 0.9863        |
+| 0.0274        | 21.6981 | 1150 | 0.0322          | 0.9675   | 0.9795        | 0.9927           | 0.9955              | 0.9464        | 0.9965             | 0.9917         | 0.9218   | 0.9890        |
+| 0.0622        | 22.6415 | 1200 | 0.0360          | 0.9648   | 0.9798        | 0.9913           | 0.9932              | 0.9512        | 0.9949             | 0.9881         | 0.9197   | 0.9868        |
+| 0.0296        | 23.5849 | 1250 | 0.0334          | 0.9670   | 0.9823        | 0.9925           | 0.9953              | 0.9567        | 0.9950             | 0.9917         | 0.9207   | 0.9885        |
+| 0.0222        | 24.5283 | 1300 | 0.0326          | 0.9674   | 0.9823        | 0.9925           | 0.9948              | 0.9569        | 0.9953             | 0.9912         | 0.9222   | 0.9887        |
+| 0.0719        | 25.4717 | 1350 | 0.0328          | 0.9671   | 0.9832        | 0.9923           | 0.9945              | 0.9603        | 0.9947             | 0.9907         | 0.9223   | 0.9883        |
+| 0.0197        | 26.4151 | 1400 | 0.0311          | 0.9681   | 0.9817        | 0.9929           | 0.9962              | 0.9537        | 0.9954             | 0.9922         | 0.9230   | 0.9893        |
+| 0.0223        | 27.3585 | 1450 | 0.0324          | 0.9664   | 0.9811        | 0.9925           | 0.9956              | 0.9527        | 0.9950             | 0.9916         | 0.9191   | 0.9885        |
+| 0.024         | 28.3019 | 1500 | 0.0340          | 0.9657   | 0.9808        | 0.9920           | 0.9950              | 0.9528        | 0.9947             | 0.9902         | 0.9190   | 0.9880        |
+| 0.0242        | 29.2453 | 1550 | 0.0325          | 0.9672   | 0.9810        | 0.9926           | 0.9953              | 0.9522        | 0.9957             | 0.9915         | 0.9212   | 0.9888        |
+| 0.0371        | 30.1887 | 1600 | 0.0315          | 0.9681   | 0.9826        | 0.9928           | 0.9957              | 0.9569        | 0.9952             | 0.9920         | 0.9232   | 0.9891        |
+| 0.0235        | 31.1321 | 1650 | 0.0370          | 0.9632   | 0.9799        | 0.9911           | 0.9937              | 0.9520        | 0.9941             | 0.9880         | 0.9150   | 0.9868        |
+| 0.0266        | 32.0755 | 1700 | 0.0335          | 0.9664   | 0.9811        | 0.9925           | 0.9951              | 0.9527        | 0.9954             | 0.9913         | 0.9193   | 0.9887        |
+| 0.0216        | 33.0189 | 1750 | 0.0344          | 0.9656   | 0.9800        | 0.9921           | 0.9946              | 0.9497        | 0.9956             | 0.9904         | 0.9182   | 0.9883        |
+| 0.0382        | 33.9623 | 1800 | 0.0319          | 0.9680   | 0.9819        | 0.9929           | 0.9954              | 0.9544        | 0.9959             | 0.9922         | 0.9224   | 0.9893        |
+| 0.0161        | 34.9057 | 1850 | 0.0336          | 0.9672   | 0.9799        | 0.9927           | 0.9955              | 0.9479        | 0.9963             | 0.9920         | 0.9206   | 0.9890        |
+| 0.0216        | 35.8491 | 1900 | 0.0336          | 0.9671   | 0.9806        | 0.9926           | 0.9956              | 0.9505        | 0.9957             | 0.9916         | 0.9208   | 0.9888        |
+### Framework versions
+- Transformers 4.41.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.19.2
+- Tokenizers 0.19.1

config.json ADDED Viewed

	@@ -0,0 +1,86 @@

+{
+  "_name_or_path": "microsoft/beit-base-finetuned-ade-640-640",
+  "add_fpn": false,
+  "architectures": [
+    "BeitForSemanticSegmentation"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "auxiliary_channels": 256,
+  "auxiliary_concat_input": false,
+  "auxiliary_loss_weight": 0.4,
+  "auxiliary_num_convs": 1,
+  "drop_path_rate": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "background",
+    "1": "melt",
+    "2": "substrate"
+  },
+  "image_size": 640,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "background": 0,
+    "melt": 1,
+    "substrate": 2
+  },
+  "layer_norm_eps": 1e-12,
+  "layer_scale_init_value": 0.1,
+  "model_type": "beit",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "out_features": [
+    "stage3",
+    "stage5",
+    "stage7",
+    "stage11"
+  ],
+  "out_indices": [
+    3,
+    5,
+    7,
+    11
+  ],
+  "patch_size": 16,
+  "pool_scales": [
+    1,
+    2,
+    3,
+    6
+  ],
+  "reshape_hidden_states": true,
+  "segmentation_indices": [
+    3,
+    5,
+    7,
+    11
+  ],
+  "semantic_loss_ignore_index": 255,
+  "stage_names": [
+    "stem",
+    "stage1",
+    "stage2",
+    "stage3",
+    "stage4",
+    "stage5",
+    "stage6",
+    "stage7",
+    "stage8",
+    "stage9",
+    "stage10",
+    "stage11",
+    "stage12"
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.2",
+  "use_absolute_position_embeddings": false,
+  "use_auxiliary_head": true,
+  "use_mask_token": false,
+  "use_mean_pooling": true,
+  "use_relative_position_bias": true,
+  "use_shared_relative_position_bias": false,
+  "vocab_size": 8192
+}

model.safetensors ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:865c0759d35134bd5b5a413eb51d352ab10ca0a4c142513948b48fcc6bb83c52
+size 653146272

training_args.bin ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:3990eb765db909c68d1ab2c42a0084d7d33606fc61f2aa6f60f413bc4c8b3722
+size 4923