maxmarcon
/

gpt2-sarcasm-defuser

@@ -1,243 +1,14 @@
 ---
 language: en
 license: mit
-base_model: gpt2
-model-index:
-- name: gpt2-sarcasm-defuser
-  results:
-  - task:
-      type: text-generation
-      name: Sarcasm Defuser
-    dataset:
-      name: Custom Sarcasm Set
-      type: custom
-    metrics:
-    - type: sarcasm_model
-      value: pn89348/sarcasm_model
-      name: Sarcasm_Model
-    - type: similarity_model
-      value: multi-qa-mpnet-base-dot-v1
-      name: Similarity_Model
-    - type: similarity_mean
-      value: 0.5433251563346747
-      name: Similarity Mean
-    - type: similarity_median
-      value: 0.543032169342041
-      name: Similarity Median
-    - type: similarity_stddev
-      value: 0.1393161231933361
-      name: Similarity Stddev
-    - type: sarcasm_prob_orig_mean
-      value: 0.09905152971094305
-      name: Sarcasm Prob Orig Mean
-    - type: sarcasm_prob_orig_median
-      value: 0.009430885314941406
-      name: Sarcasm Prob Orig Median
-    - type: sarcasm_prob_orig_stddev
-      value: 0.23873868066866977
-      name: Sarcasm Prob Orig Stddev
-    - type: sarcasm_prob_gen_mean
-      value: 0.23069801643641308
-      name: Sarcasm Prob Gen Mean
-    - type: sarcasm_prob_gen_median
-      value: 0.06437027454376221
-      name: Sarcasm Prob Gen Median
-    - type: sarcasm_prob_gen_stddev
-      value: 0.28822486759950117
-      name: Sarcasm Prob Gen Stddev
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
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-- **Language(s) (NLP):** en
-- **License:** mit
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-### Model Sources [optional]
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-## Uses
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-### Direct Use
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-## How to Get Started with the Model
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-#### Preprocessing [optional]
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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 -->
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-## Evaluation
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-### Testing Data, Factors & Metrics
-#### Testing Data
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-#### Factors
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-#### Metrics
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-### Results
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-#### Summary
-## Model Examination [optional]
-<!-- Relevant interpretability work for the model goes here -->
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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).
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 ---
+base_model: gpt2
 language: en
 license: mit
+metrics:
+- sarcasm
+- similarity
+pretty_name: GP2 Sarcasm Defuser
 ---
+# GP2 Sarcasm Defuser
+#  ## How to use:
+Coming soon