End of training

README.md

@@ -1,199 +1,105 @@
 ---
-library_name: transformers
-tags: []
+license: other
+base_model: nvidia/segformer-b1-finetuned-ade-512-512
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+metrics:
+- precision
+model-index:
+- name: segformer_b1_finetuned_segment_pv_p100_32batch
+  results: []
 ---
 
-# 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]
+<!-- 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. -->
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mouadn773/segformer-pv-4batches/runs/l37rzbqs)
+# segformer_b1_finetuned_segment_pv_p100_32batch
+
+This model is a fine-tuned version of [nvidia/segformer-b1-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b1-finetuned-ade-512-512) on the mouadenna/satellite_PV_dataset_train_test_v1 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0059
+- Mean Iou: 0.8651
+- Precision: 0.9226
+
+## 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: 0.00032
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 40
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Precision |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|
+| 0.4433        | 1.0   | 115  | 0.1593          | 0.5991   | 0.6512    |
+| 0.0857        | 2.0   | 230  | 0.0270          | 0.7731   | 0.8493    |
+| 0.0201        | 3.0   | 345  | 0.0116          | 0.8058   | 0.8974    |
+| 0.0108        | 4.0   | 460  | 0.0084          | 0.8146   | 0.8758    |
+| 0.0077        | 5.0   | 575  | 0.0070          | 0.8267   | 0.8871    |
+| 0.0059        | 6.0   | 690  | 0.0072          | 0.8241   | 0.9128    |
+| 0.0051        | 7.0   | 805  | 0.0058          | 0.8433   | 0.9197    |
+| 0.0044        | 8.0   | 920  | 0.0059          | 0.8466   | 0.8994    |
+| 0.0042        | 9.0   | 1035 | 0.0055          | 0.8474   | 0.9075    |
+| 0.0037        | 10.0  | 1150 | 0.0054          | 0.8576   | 0.9100    |
+| 0.0033        | 11.0  | 1265 | 0.0056          | 0.8555   | 0.9254    |
+| 0.0032        | 12.0  | 1380 | 0.0059          | 0.8455   | 0.8795    |
+| 0.0032        | 13.0  | 1495 | 0.0055          | 0.8600   | 0.9226    |
+| 0.0033        | 14.0  | 1610 | 0.0057          | 0.8558   | 0.9234    |
+| 0.0029        | 15.0  | 1725 | 0.0063          | 0.8533   | 0.9211    |
+| 0.003         | 16.0  | 1840 | 0.0072          | 0.8498   | 0.9261    |
+| 0.0035        | 17.0  | 1955 | 0.0102          | 0.7815   | 0.9482    |
+| 0.0033        | 18.0  | 2070 | 0.0244          | 0.5662   | 0.9688    |
+| 0.0028        | 19.0  | 2185 | 0.0256          | 0.5643   | 0.9675    |
+| 0.0027        | 20.0  | 2300 | 0.0078          | 0.8405   | 0.9370    |
+| 0.0026        | 21.0  | 2415 | 0.0241          | 0.6404   | 0.9706    |
+| 0.0024        | 22.0  | 2530 | 0.0492          | 0.3084   | 0.9702    |
+| 0.0025        | 23.0  | 2645 | 0.1065          | 0.0107   | 0.9109    |
+| 0.0024        | 24.0  | 2760 | 0.0958          | 0.0374   | 0.8273    |
+| 0.003         | 25.0  | 2875 | 0.0571          | 0.1779   | 0.9912    |
+| 0.0026        | 26.0  | 2990 | 0.0968          | 0.0140   | 0.9839    |
+| 0.0023        | 27.0  | 3105 | 0.0454          | 0.2833   | 0.9702    |
+| 0.0022        | 28.0  | 3220 | 0.0519          | 0.2828   | 0.9658    |
+| 0.0021        | 29.0  | 3335 | 0.0446          | 0.3157   | 0.9698    |
+| 0.002         | 30.0  | 3450 | 0.0415          | 0.3630   | 0.9702    |
+| 0.002         | 31.0  | 3565 | 0.0308          | 0.4995   | 0.9737    |
+| 0.002         | 32.0  | 3680 | 0.0227          | 0.6260   | 0.9700    |
+| 0.0019        | 33.0  | 3795 | 0.0131          | 0.7631   | 0.9631    |
+| 0.0019        | 34.0  | 3910 | 0.0102          | 0.8131   | 0.9541    |
+| 0.0021        | 35.0  | 4025 | 0.0058          | 0.8450   | 0.9449    |
+| 0.0018        | 36.0  | 4140 | 0.0073          | 0.8556   | 0.9326    |
+| 0.0019        | 37.0  | 4255 | 0.0060          | 0.8601   | 0.9339    |
+| 0.0018        | 38.0  | 4370 | 0.0060          | 0.8654   | 0.9244    |
+| 0.0019        | 39.0  | 4485 | 0.0061          | 0.8636   | 0.9248    |
+| 0.0017        | 40.0  | 4600 | 0.0059          | 0.8651   | 0.9226    |
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.1.2
+- Datasets 2.20.0
+- Tokenizers 0.19.1

config.json

@@ -0,0 +1,78 @@
+{
+  "_name_or_path": "nvidia/segformer-b1-finetuned-ade-512-512",
+  "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": [
+    64,
+    128,
+    320,
+    512
+  ],
+  "id2label": {
+    "0": "unlabeled",
+    "1": "PV"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "PV": 1,
+    "unlabeled": 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": "4.42.3"
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a3e09e1948e74d1cbd4dc78c7d9c9ddf8334af74aa19398a73f4ff160f56d5d9
+size 54737376

runs/Aug02_00-21-22_c65165ea633d/events.out.tfevents.1722558104.c65165ea633d.24.0

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:70dabbd6e70f585254b84578b67040890d11483fee9dbc982f581f77bef65090
+size 29285

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0cc59d2b0103c480aab787fb03aff65bbffae4bed0a08bdb61685633e940ee68
+size 5176