Add SetFit model

README.md

@@ -1,5 +1,5 @@
 ---
-base_model: HSLU-AICOMP-LearningAgencyLab/automated-essay-scoring-setfit
+base_model: HSLU-AICOMP-LearningAgencyLab/automated-essay-scoring-setfit-finetuned
 library_name: setfit
 metrics:
 - accuracy
@@ -13,9 +13,9 @@ widget: []
 inference: true
 ---
 
-# SetFit with HSLU-AICOMP-LearningAgencyLab/automated-essay-scoring-setfit
+# SetFit with HSLU-AICOMP-LearningAgencyLab/automated-essay-scoring-setfit-finetuned
 
-This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [HSLU-AICOMP-LearningAgencyLab/automated-essay-scoring-setfit](https://huggingface.co/HSLU-AICOMP-LearningAgencyLab/automated-essay-scoring-setfit) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification.
+This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [HSLU-AICOMP-LearningAgencyLab/automated-essay-scoring-setfit-finetuned](https://huggingface.co/HSLU-AICOMP-LearningAgencyLab/automated-essay-scoring-setfit-finetuned) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification.
 
 The model has been trained using an efficient few-shot learning technique that involves:
 
@@ -26,7 +26,7 @@ The model has been trained using an efficient few-shot learning technique that i
 
 ### Model Description
 - **Model Type:** SetFit
-- **Sentence Transformer body:** [HSLU-AICOMP-LearningAgencyLab/automated-essay-scoring-setfit](https://huggingface.co/HSLU-AICOMP-LearningAgencyLab/automated-essay-scoring-setfit)
+- **Sentence Transformer body:** [HSLU-AICOMP-LearningAgencyLab/automated-essay-scoring-setfit-finetuned](https://huggingface.co/HSLU-AICOMP-LearningAgencyLab/automated-essay-scoring-setfit-finetuned)
 - **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance
 - **Maximum Sequence Length:** 4098 tokens
 <!-- - **Number of Classes:** Unknown -->
@@ -108,10 +108,10 @@ preds = model("I loved the spiderman movie!")
 ### Training Results
 | Epoch  | Step  | Training Loss | Validation Loss |
 |:------:|:-----:|:-------------:|:---------------:|
-| 0.0001 | 1     | 0.0985        | -               |
-| 1.0    | 17255 | 0.0833        | 0.2395          |
-| 2.0    | 34510 | 0.0206        | 0.2721          |
-| 3.0    | 51765 | 0.0018        | 0.2730          |
+| 0.0001 | 1     | 0.1068        | -               |
+| 1.0    | 17262 | 0.0417        | 0.1646          |
+| 2.0    | 34524 | 0.0201        | 0.1933          |
+| 3.0    | 51786 | 0.0018        | 0.1968          |
 
 ### Framework Versions
 - Python: 3.11.9

model_head.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:33ea98c1fb86bdf14dae4dd8fce1d6f9b73bc9e902deeeed43ee7c3d7688d3e2
 size 37799