nemik
/

frost-mobile-apple__mobilevit-xx-small-v2024-10-22

@@ -1,199 +1,109 @@
 ---
 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: apple/mobilevit-xx-small
+tags:
+- generated_from_trainer
+datasets:
+- webdataset
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: frost-mobile-apple__mobilevit-xx-small-v2024-10-22
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: webdataset
+      type: webdataset
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9497777777777778
+    - name: F1
+      type: f1
+      value: 0.8754134509371555
+    - name: Precision
+      type: precision
+      value: 0.8744493392070485
+    - name: Recall
+      type: recall
+      value: 0.8763796909492274
 ---
+<!-- 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. -->
+# frost-mobile-apple__mobilevit-xx-small-v2024-10-22
+This model is a fine-tuned version of [apple/mobilevit-xx-small](https://huggingface.co/apple/mobilevit-xx-small) on the webdataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1343
+- Accuracy: 0.9498
+- F1: 0.8754
+- Precision: 0.8744
+- Recall: 0.8764
+## 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: 0.0002
+- train_batch_size: 16
+- eval_batch_size: 8
+- 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: 30
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.1927        | 1.7544  | 100  | 0.1470          | 0.9422   | 0.8565 | 0.8565    | 0.8565 |
+| 0.1601        | 3.5088  | 200  | 0.1499          | 0.9444   | 0.8616 | 0.8644    | 0.8587 |
+| 0.1544        | 5.2632  | 300  | 0.1536          | 0.9391   | 0.8493 | 0.8465    | 0.8521 |
+| 0.207         | 7.0175  | 400  | 0.1374          | 0.9436   | 0.8575 | 0.8721    | 0.8433 |
+| 0.1709        | 8.7719  | 500  | 0.1443          | 0.9431   | 0.8587 | 0.8587    | 0.8587 |
+| 0.1548        | 10.5263 | 600  | 0.1572          | 0.9387   | 0.8490 | 0.8416    | 0.8565 |
+| 0.1802        | 12.2807 | 700  | 0.1436          | 0.9458   | 0.8656 | 0.8637    | 0.8675 |
+| 0.1455        | 14.0351 | 800  | 0.1442          | 0.9467   | 0.8667 | 0.8725    | 0.8609 |
+| 0.1514        | 15.7895 | 900  | 0.1500          | 0.9422   | 0.8571 | 0.8534    | 0.8609 |
+| 0.1368        | 17.5439 | 1000 | 0.1391          | 0.9489   | 0.8718 | 0.8806    | 0.8631 |
+| 0.1515        | 19.2982 | 1100 | 0.1370          | 0.9476   | 0.8700 | 0.8681    | 0.8720 |
+| 0.1372        | 21.0526 | 1200 | 0.1393          | 0.9458   | 0.8644 | 0.8702    | 0.8587 |
+| 0.1397        | 22.8070 | 1300 | 0.1359          | 0.9498   | 0.8746 | 0.8795    | 0.8698 |
+| 0.1398        | 24.5614 | 1400 | 0.1352          | 0.9489   | 0.8740 | 0.8674    | 0.8808 |
+| 0.1276        | 26.3158 | 1500 | 0.1381          | 0.9476   | 0.8700 | 0.8681    | 0.8720 |
+| 0.1519        | 28.0702 | 1600 | 0.1380          | 0.9462   | 0.8666 | 0.8656    | 0.8675 |
+| 0.1479        | 29.8246 | 1700 | 0.1343          | 0.9498   | 0.8754 | 0.8744    | 0.8764 |
+### Framework versions
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.2
+- Tokenizers 0.19.1

runs/Oct22_16-09-06_2ae384978577/events.out.tfevents.1729613380.2ae384978577.344.2 CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c44f9c9c80ea1953e68eb99983cc8b7d4702be9b376ac88b949640aa7ea72c18
-size 44420

 version https://git-lfs.github.com/spec/v1
+oid sha256:7ced51cc713ae0d67a9bd7b2cc26aa85903e81633b9bd9a0ce8d88527b399f55
+size 50149