Update README.md

README.md

@@ -24,13 +24,10 @@ We have applied LoRA to adapt the original RoBERTa model to the specific nuances
 LoRA introduces low-rank matrices that are trained during the fine-tuning process, enabling the model to learn task-specific 
 adaptations without altering the pre-trained weights directly.
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
+- **Developed by:** Likhith231
+- **Model type:** Text Classification
 - **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+- **Finetuned from model:** Roberta Base
 
 ### Model Sources [optional]
 
@@ -50,23 +47,6 @@ adaptations without altering the pre-trained weights directly.
 
 [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 -->
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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]
 
 ### Recommendations
 
@@ -82,129 +62,34 @@ Use the code below to get started with the model.
 
 ## 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. -->
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-[More Information Needed]
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-### Training Procedure 
-
-<!-- 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
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+model= Roberta-base
+all params =  67,584,004 
+trainable params=  628,994 
+trainable% = 0.9306847223789819
 
-#### 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
-
-<!-- This section describes the evaluation protocols and provides the results. -->
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-### Testing Data, Factors & Metrics
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-#### Testing Data
-
-<!-- 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
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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-[More Information Needed]
+### Parameters
+weight_decay = 0.01
+lr = 1e-3
+batch_size = 4
+num_epochs = 10
 
 ### Results
 
-[More Information Needed]
-
-#### Summary
-
+Epoch|Training Loss|Validation Loss|Accuracy
+---------------------------------------------
+1|No log|0.172788|{'accuracy': 0.957}
+2|0.194500|0.202991|{'accuracy': 0.956}
+3|0.194500|0.229950|{'accuracy': 0.958}
+4|0.038400|0.267390|{'accuracy': 0.954}
+5|0.038400|0.283116|{'accuracy': 0.963}
+6|0.007000|0.254960|{'accuracy': 0.961}
+7|0.007000|0.299375|{'accuracy': 0.961}
+8|0.007900|0.276321|{'accuracy': 0.966}
+9|0.007900|0.275304|{'accuracy': 0.967}
+10|0.002000|0.271234|{'accuracy': 0.967}
+10|0.002000|0.271234|{'accuracy': 0.967}
 
 
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
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-## 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]
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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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-#### Hardware
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-#### Software
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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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-**APA:**
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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 [optional]
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-## Model Card Authors [optional]
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-## Model Card Contact
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-
 
 ### Framework versions