orth

README.md

@@ -5,11 +5,11 @@ tags:
 - evaluate
 - metric
 description: >-
-  ParaPLUIE is a metric for evaluating the semantic proximity of two sentences. 
-  ParaPLUIE use the perplexity of an LLM to compute a confidence score. It has
-  shown the highest correlation with human judgement on paraphrase
-  classification meanwhile reamin the computional cost low as it roughtly equal
-  to one token generation cost.
+  ParaPLUIE is a metric for evaluating the semantic proximity between two sentences. 
+  ParaPLUIE uses the perplexity of an LLM to compute a confidence score. It has
+  shown the highest correlation with human judgment on paraphrase
+  classification while maintaining a low computational cost, as it roughly equivalent
+  to the cost of generating a single token.
 sdk: gradio
 sdk_version: 3.19.1
 app_file: app.py
@@ -20,13 +20,13 @@ short_description: ParaPLUIE is a metric for evaluating the semantic proximity
 # Metric Card for ParaPLUIE (Paraphrase Generation Evaluation Powered by an LLM)
 
 ## Metric Description
-ParaPLUIE is a metric for evaluating the semantic proximity of two sentences. 
-ParaPLUIE use the perplexity of an LLM to compute a confidence score.
-It has shown the highest correlation with human judgement on paraphrase classification meanwhile reamin the computional cost low as it roughtly equal to one token generation cost.
+ParaPLUIE is a metric for evaluating the semantic proximity between two sentences. 
+ParaPLUIE uses the perplexity of an LLM to compute a confidence score.
+It has shown the highest correlation with human judgment on paraphrase classification while maintaining a low computational cost, as it roughly equivalent to the cost of generating a single token.
 
 ## How to Use
 
-This metric requires a source sentence and it's hypothetical paraphrase.
+This metric requires a source sentence and its hypothetical paraphrase.
 
 ```python
 import evaluate
@@ -46,9 +46,9 @@ print(results)
 
 ### Output Values
 
-- **score** (`float`): ParaPLUIE score. Minimum possible value is -inf. Maximum possible value is +inf. A score greater than 0 mean that sentences are paraphrases. A score lower than 0 mean the opposite.
+- **score** (`float`): ParaPLUIE score. Minimum possible value is -inf. Maximum possible value is +inf. A score greater than 0 means that sentences are paraphrases. A score lower than 0 indicates the opposite.
 
-This metric outputs a dictionary, containing the score.
+This metric outputs a dictionary containing the score.
 
 ### Examples
 
@@ -76,7 +76,7 @@ ppluie.init(
 )
 ```
 
-show available prompting templates
+Show the available prompting templates
 ```python
 ppluie.show_templates()
 >>> DIRECT
@@ -90,7 +90,7 @@ ppluie.show_templates()
 >>> NETWORK
 ```
 
-show LLM already tested with ParaPLUIE
+Show the LLMs that have already been tested with ParaPLUIE
 ```python
 ppluie.show_available_models()
 >>> HuggingFaceTB/SmolLM2-135M-Instruct
@@ -112,18 +112,18 @@ ppluie.show_available_models()
 >>> CohereForAI/c4ai-command-r-08-2024
 ```
 
-change prompting template
+Change the prompting template
 ```python
 ppluie.setTemplate("DIRECT")
 ```
 
-show how is the prompt encoded, to ensure that the correct numbers of special tokens are removed and Yes / No words fit on one token
+Show how the prompt is encoded to ensure that the correct numbers of special tokens are removed and that the words "Yes" and "No" each fit into a single token
 ```python
 ppluie.check_end_tokens_tmpl()
 ```
 
 ## Limitations and Bias
-This metric is based on an LLM and therefore is limited by the LLM used.
+This metric is based on an LLM and is therefore limited by the LLM that is used.
 
 ## Source code
 [GitLab](https://gitlab.inria.fr/expression/paraphrase-generation-evaluation-powered-by-an-llm-a-semantic-metric-not-a-lexical-one-coling-2025)