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roberta-base on a news dataset for news source classification. It predicts the source or publisher of a news article (e.g., CNN, BBC, Reuters, etc.). Fine-tuning was done using grid search across multiple hyperparameters to identify the best configuration for performance.roberta-basesafetensors1from transformers import pipeline
2
3classifier = pipeline("text-classification", model="VridhiJain/roberta_gridsearch_2")
4classifier("Breaking: Central bank raises interest rates amid inflation fears.")
5
6
7- **Developed by:** Vridhi Jain
8- **Model type:** RoBERTa
9- **Language(s) (NLP):** English
10- **License:** apache-2.0
11- **Finetuned from model [optional]:** roberta-base
12
13### Model Sources [optional]
14
15<!-- Provide the basic links for the model. -->
16
17- **Repository:** [More Information Needed]
18- **Paper [optional]:** [More Information Needed]
19- **Demo [optional]:** [More Information Needed]
20
21## Uses
22
23Text Classification: News Sources
24
25### Direct Use
26
27<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
28
29[More Information Needed]
30
31### Downstream Use [optional]
32
33<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
34
35[More Information Needed]
36
37### Out-of-Scope Use
38
39<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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41[More Information Needed]
42
43## Bias, Risks, and Limitations
44
45<!-- This section is meant to convey both technical and sociotechnical limitations. -->
46
47[More Information Needed]
48
49### Recommendations
50
51<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
52
53Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
54
55## How to Get Started with the Model
56
57Use the code below to get started with the model.
58
59[More Information Needed]
60
61## Training Details
62
63### Training Data
64
65<!-- 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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67[More Information Needed]
68
69### Training Procedure
70
71<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
72
73#### Preprocessing [optional]
74
75[More Information Needed]
76
77
78#### Training Hyperparameters
79
80- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
81
82#### Speeds, Sizes, Times [optional]
83
84<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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86[More Information Needed]
87
88## Evaluation
89
90<!-- This section describes the evaluation protocols and provides the results. -->
91
92### Testing Data, Factors & Metrics
93
94#### Testing Data
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96<!-- This should link to a Dataset Card if possible. -->
97
98[More Information Needed]
99
100#### Factors
101
102<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
103
104[More Information Needed]
105
106#### Metrics
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108<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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110[More Information Needed]
111
112### Results
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114[More Information Needed]
115
116#### Summary
117
118
119
120## Model Examination [optional]
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122<!-- Relevant interpretability work for the model goes here -->
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124[More Information Needed]
125
126## Environmental Impact
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128<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
129
130Carbon 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).
131
132- **Hardware Type:** [More Information Needed]
133- **Hours used:** [More Information Needed]
134- **Cloud Provider:** [More Information Needed]
135- **Compute Region:** [More Information Needed]
136- **Carbon Emitted:** [More Information Needed]
137
138## Technical Specifications [optional]
139
140### Model Architecture and Objective
141
142[More Information Needed]
143
144### Compute Infrastructure
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146[More Information Needed]
147
148#### Hardware
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150[More Information Needed]
151
152#### Software
153
154[More Information Needed]
155
156## Citation [optional]
157
158<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
159
160**BibTeX:**
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163
164**APA:**
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167
168## Glossary [optional]
169
170<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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172[More Information Needed]
173
174## More Information [optional]
175
176[More Information Needed]
177
178## Model Card Authors [optional]
179
180[More Information Needed]
181
182## Model Card Contact
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184[More Information Needed]