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Push model using huggingface_hub.

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  1. README.md +6 -199
  2. config.json +3 -45
  3. model.safetensors +2 -2
README.md CHANGED
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  ---
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- base_model: bert-base-uncased-pruned
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- datasets:
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- - QuotaClimat/frugalaichallenge-text-train
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- language:
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- - en
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- license: mit
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- model_name: frugal_ai_bert_base_pruned
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- pipeline_tag: text-classification
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  ---
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- # Model Card for Model ID
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- <!-- Provide a quick summary of what the model is/does. -->
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- Climate disinformation classifier
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- ## Model Details
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- ### Model Description
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- <!-- Provide a longer summary of what this model is. -->
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- Pruned BERT model fine-tuned on the FrugalAI Challenge dataset. Pruning was carried out using a linear prune scheduler.
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- - **Developed by:** Terry Zhang
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- - **Shared by [optional]:** Terry Zhang
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- - **Model type:** Text classification
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- - **License:** mit
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- - **Finetuned from model [optional]:** bert-base-uncased
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- ### Model Sources [optional]
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- <!-- Provide the basic links for the model. -->
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- - **Repository:** frugal_ai_bert_base_pruned
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- ## Uses
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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- ### Direct Use
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- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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- [More Information Needed]
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- ### Downstream Use [optional]
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- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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- [More Information Needed]
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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- [More Information Needed]
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- ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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- ### Recommendations
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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- ## How to Get Started with the Model
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- Use the code below to get started with the model.
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- [More Information Needed]
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- ## Training Details
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- ### Training Data
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- <!-- 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. -->
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- [More Information Needed]
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- ### Training Procedure
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- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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- #### Preprocessing [optional]
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- [More Information Needed]
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- #### Training Hyperparameters
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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- #### Speeds, Sizes, Times [optional]
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- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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- [More Information Needed]
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- ## Evaluation
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- <!-- This section describes the evaluation protocols and provides the results. -->
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- ### Testing Data, Factors & Metrics
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- #### Testing Data
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- <!-- This should link to a Dataset Card if possible. -->
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- [More Information Needed]
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- #### Factors
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- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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- [More Information Needed]
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- #### Metrics
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- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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- [More Information Needed]
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- ### Results
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- [More Information Needed]
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- #### Summary
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- ## Model Examination [optional]
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- <!-- Relevant interpretability work for the model goes here -->
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- [More Information Needed]
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- ## Environmental Impact
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- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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- 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).
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- - **Hardware Type:** [More Information Needed]
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- - **Hours used:** [More Information Needed]
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- - **Cloud Provider:** [More Information Needed]
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- - **Compute Region:** [More Information Needed]
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- - **Carbon Emitted:** [More Information Needed]
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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- [More Information Needed]
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- ### Compute Infrastructure
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- [More Information Needed]
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- #### Hardware
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- [More Information Needed]
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- #### Software
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- [More Information Needed]
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- ## Citation [optional]
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- <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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- **BibTeX:**
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- [More Information Needed]
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- **APA:**
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- [More Information Needed]
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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- [More Information Needed]
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- ## More Information [optional]
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- [More Information Needed]
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- ## Model Card Authors [optional]
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- [More Information Needed]
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- ## Model Card Contact
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- [More Information Needed]
 
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  ---
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+ tags:
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+ - model_hub_mixin
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+ - pytorch_model_hub_mixin
 
 
 
 
 
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  ---
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+ This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
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+ - Library: [More Information Needed]
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+ - Docs: [More Information Needed]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
config.json CHANGED
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  {
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- "_name_or_path": "bert-base-uncased",
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- "architectures": [
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- "BertModel"
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- ],
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- "attention_probs_dropout_prob": 0.1,
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- "classifier_dropout": null,
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- "gradient_checkpointing": false,
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- "hidden_act": "gelu",
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- "hidden_dropout_prob": 0.1,
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- "hidden_size": 768,
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- "id2label": {
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- "0": "LABEL_0",
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- "1": "LABEL_1",
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- "2": "LABEL_2",
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- "3": "LABEL_3",
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- "4": "LABEL_4",
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- "5": "LABEL_5",
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- "6": "LABEL_6",
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- "7": "LABEL_7"
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- },
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- "initializer_range": 0.02,
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- "intermediate_size": 3072,
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- "label2id": {
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- "LABEL_0": 0,
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- "LABEL_1": 1,
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- "LABEL_3": 3,
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- "LABEL_4": 4,
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- "LABEL_6": 6,
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- "LABEL_7": 7
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- },
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- "layer_norm_eps": 1e-12,
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- "max_position_embeddings": 512,
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- "model_type": "bert",
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- "num_attention_heads": 12,
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- "num_hidden_layers": 12,
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- "pad_token_id": 0,
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- "position_embedding_type": "absolute",
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- "torch_dtype": "float32",
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- "transformers_version": "4.45.2",
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- "type_vocab_size": 2,
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- "use_cache": true,
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- "vocab_size": 30522
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- }
 
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  {
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+ "bert_variety": "bert-base-uncased",
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+ "num_labels": 8
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+ }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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