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Upload RobertaForSequenceClassification

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  1. README.md +199 -0
  2. config.json +74 -34
  3. model.safetensors +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ tags: []
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+ ---
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+
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+ # Model Card for Model ID
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
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+ ## Model Details
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+
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+ ### Model Description
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+
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+ <!-- Provide a longer summary of what this model is. -->
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+ This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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+
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+ - **Developed by:** [More Information Needed]
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+ - **Funded by [optional]:** [More Information Needed]
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+ - **Shared by [optional]:** [More Information Needed]
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+ - **Model type:** [More Information Needed]
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+ - **Language(s) (NLP):** [More Information Needed]
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+ - **License:** [More Information Needed]
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+ - **Finetuned from model [optional]:** [More Information Needed]
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+
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+ ### Model Sources [optional]
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+
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+ <!-- Provide the basic links for the model. -->
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+ - **Repository:** [More Information Needed]
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+ - **Paper [optional]:** [More Information Needed]
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+ - **Demo [optional]:** [More Information Needed]
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+
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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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+
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+ ### Direct Use
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+
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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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+
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+ ### Downstream Use [optional]
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+
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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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+
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+ ### Out-of-Scope Use
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+
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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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+
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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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+
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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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+
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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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+
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+ ## Training Details
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+
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+ ### Training Data
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+
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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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+
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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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+
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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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+
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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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+
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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]
config.json CHANGED
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  {
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- "_name_or_path": "model/bea_classifier",
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  "architectures": [
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  "RobertaForSequenceClassification"
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  ],
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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": "Acquisition",
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- "1": "Company_Invest",
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- "2": "Contract",
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- "3": "Government_Invest",
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- "4": "Market_Outlook",
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- "5": "New_Product",
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- "6": "Other",
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- "7": "Partnership",
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- "8": "Sell",
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- "9": "Supply_Environment",
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- "10": "Economic_Trend",
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- "11": "Company_Other",
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- "12": "Regulation",
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- "13": "Company_Finance",
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- "14": "Tech_Adaptation",
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- "15": "Company_Patent"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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- "Acquisition": 0,
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- "Company_Finance": 13,
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- "Company_Invest": 1,
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- "Company_Other": 11,
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- "Company_Patent": 15,
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- "Contract": 2,
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- "Economic_Trend": 10,
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- "Government_Invest": 3,
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- "Market_Outlook": 4,
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- "New_Product": 5,
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- "Other": 6,
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- "Partnership": 7,
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- "Regulation": 12,
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- "Sell": 8,
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- "Supply_Environment": 9,
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- "Tech_Adaptation": 14
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  },
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  "layer_norm_eps": 1e-05,
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  "max_position_embeddings": 514,
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  "position_embedding_type": "absolute",
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  "problem_type": "single_label_classification",
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  "torch_dtype": "float32",
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- "transformers_version": "4.31.0",
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  "type_vocab_size": 1,
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  "use_cache": true,
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  "vocab_size": 50265
 
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  {
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+ "_name_or_path": "model/bea_classifier_v2.1_36",
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  "architectures": [
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  "RobertaForSequenceClassification"
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  ],
 
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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": "Academic_Activity",
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+ "1": "Acquisition",
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+ "2": "Art_Culture",
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+ "3": "Company_Company_Partnership",
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+ "4": "Company_Compliance_Issues",
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+ "5": "Company_Contract",
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+ "6": "Company_Event",
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+ "7": "Company_Finance",
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+ "8": "Company_Governance",
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+ "9": "Company_Insight",
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+ "10": "Company_Invest",
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+ "11": "Company_Government_Partnership",
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+ "12": "Company_Patent",
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+ "13": "Company_Product_Stop",
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+ "14": "Company_Sale",
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+ "15": "Company_Startup",
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+ "16": "Company_Supply_Disruption",
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+ "17": "Company_Workforce_Dynamic",
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+ "18": "Competitive_Landscape",
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+ "19": "Crypto",
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+ "20": "Disaster_ManMade",
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+ "21": "Disaster_Natural",
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+ "22": "Economic_Indicator_Lagging",
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+ "23": "Economic_Indicator_Leading",
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+ "24": "Government_Invest",
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+ "25": "Government_Policy",
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+ "26": "Government_Politic",
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+ "27": "Market_Outlook",
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+ "28": "Other",
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+ "29": "Product_Issues",
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+ "30": "Product_Release",
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+ "31": "Product_Rumor",
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+ "32": "Product_Upgrade",
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+ "33": "Sport",
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+ "34": "Supply_Environment",
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+ "35": "Technology_Usecase"
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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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+ "Academic_Activity": 0,
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+ "Acquisition": 1,
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+ "Art_Culture": 2,
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+ "Company_Company_Partnership": 3,
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+ "Company_Compliance_Issues": 4,
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+ "Company_Contract": 5,
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+ "Company_Sale": 14,
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+ "Company_Workforce_Dynamic": 17,
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+ "Competitive_Landscape": 18,
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+ "Crypto": 19,
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+ "Disaster_ManMade": 20,
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+ "Market_Outlook": 27,
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+ "Other": 28,
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+ "Product_Issues": 29,
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+ "Product_Release": 30,
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+ "Product_Upgrade": 32,
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+ "Sport": 33,
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+ "Supply_Environment": 34,
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+ "Technology_Usecase": 35
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  },
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  "layer_norm_eps": 1e-05,
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  "max_position_embeddings": 514,
 
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  "position_embedding_type": "absolute",
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  "problem_type": "single_label_classification",
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  "torch_dtype": "float32",
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+ "transformers_version": "4.38.2",
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  "type_vocab_size": 1,
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  "use_cache": true,
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  "vocab_size": 50265
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