Add SetFit model

README.md

@@ -8,20 +8,18 @@ tags:
 metrics:
 - accuracy
 widget:
-- text: In these circumstances, only clearly identifiable recidivism rates were included
-    in the study.
-- text: Semi-automatic tools have been developed to aid in the processing of these
-    representations.
-- text: The purpose of this paper is to estimate the Certain Coefficient for generalized
-    Starlike functions with reference to symmetric points described on the open unit
-    disk for which R k λ ,δ (φ ) of normalized analytic functions f (z) that lies
-    in a region with reference to 1 and symmetric with reference to the real axis.
-- text: The other two SNPs were selected on the basis of the linkage disequilibrium
-    (LD) structure of the gene, allele frequency, and available Haplotype Map data
-    (http://hapmap.
-- text: It might be possible to formulate a general condition in this sense similar
-    to the condition on the Runge-Kutta methods but at present we do not know whether
-    such a condition actually exists.
+- text: For example, we cannot conclusively rule out the possibility that the five
+    wedges represent more than five seismic slip events.
+- text: Therefore the improvement of Aceclofenac dissolution is an important issue
+    for enhancing its onset of action and therapeutic efficacy.
+- text: After removal of protists and in situ incubations in dialysis bags, members
+    of the beta I clade increased to almost 30% of total cells within 24 h. It is
+    thus likely that these bacteria contributed disproportionally to the flux of organic
+    carbon from the picoplankton to the higher trophic levels.
+- text: At the conclusion of the study, participants were asked to comment on the
+    purpose of the&study.
+- text: It is therefore likely that many PEV chargers will trip in the 0.20-0.25 s
+    time frame.
 pipeline_tag: text-classification
 inference: true
 base_model: jinaai/jina-embeddings-v2-base-en
@@ -37,7 +35,7 @@ model-index:
       split: test
     metrics:
     - type: accuracy
-      value: 0.9629629629629629
+      value: 0.9777777777777777
       name: Accuracy
 ---
 
@@ -86,7 +84,7 @@ The model has been trained using an efficient few-shot learning technique that i
 ### Metrics
 | Label   | Accuracy |
 |:--------|:---------|
-| **all** | 0.9630   |
+| **all** | 0.9778   |
 
 ## Uses
 
@@ -106,7 +104,7 @@ from setfit import SetFitModel
 # Download from the 🤗 Hub
 model = SetFitModel.from_pretrained("Corran/Jina_Sci")
 # Run inference
-preds = model("Semi-automatic tools have been developed to aid in the processing of these representations.")
+preds = model("It is therefore likely that many PEV chargers will trip in the 0.20-0.25 s time frame.")
 ```
 
 <!--
@@ -138,26 +136,26 @@ preds = model("Semi-automatic tools have been developed to aid in the processing
 ### Training Set Metrics
 | Training set | Min | Median  | Max |
 |:-------------|:----|:--------|:----|
-| Word count   | 5   | 26.5079 | 98  |
+| Word count   | 5   | 25.0778 | 98  |
 
 | Label | Training Sample Count |
 |:------|:----------------------|
-| 1     | 14                    |
-| 2     | 14                    |
-| 3     | 14                    |
-| 4     | 14                    |
-| 5     | 14                    |
-| 6     | 14                    |
-| 7     | 14                    |
-| 8     | 14                    |
-| 9     | 14                    |
+| 1     | 30                    |
+| 2     | 30                    |
+| 3     | 30                    |
+| 4     | 30                    |
+| 5     | 30                    |
+| 6     | 30                    |
+| 7     | 30                    |
+| 8     | 30                    |
+| 9     | 30                    |
 
 ### Training Hyperparameters
 - batch_size: (15, 15)
 - num_epochs: (1, 1)
 - max_steps: -1
 - sampling_strategy: oversampling
-- num_iterations: 10
+- num_iterations: 30
 - body_learning_rate: (2e-05, 2e-05)
 - head_learning_rate: 2e-05
 - loss: CosineSimilarityLoss
@@ -173,10 +171,28 @@ preds = model("Semi-automatic tools have been developed to aid in the processing
 ### Training Results
 | Epoch  | Step | Training Loss | Validation Loss |
 |:------:|:----:|:-------------:|:---------------:|
-| 0.0060 | 1    | 0.2498        | -               |
-| 0.2976 | 50   | 0.1831        | -               |
-| 0.5952 | 100  | 0.1186        | -               |
-| 0.8929 | 150  | 0.048         | -               |
+| 0.0009 | 1    | 0.2692        | -               |
+| 0.0463 | 50   | 0.2293        | -               |
+| 0.0926 | 100  | 0.1244        | -               |
+| 0.1389 | 150  | 0.1245        | -               |
+| 0.1852 | 200  | 0.0595        | -               |
+| 0.2315 | 250  | 0.0102        | -               |
+| 0.2778 | 300  | 0.0042        | -               |
+| 0.3241 | 350  | 0.0036        | -               |
+| 0.3704 | 400  | 0.0031        | -               |
+| 0.4167 | 450  | 0.0015        | -               |
+| 0.4630 | 500  | 0.0007        | -               |
+| 0.5093 | 550  | 0.0008        | -               |
+| 0.5556 | 600  | 0.0008        | -               |
+| 0.6019 | 650  | 0.0006        | -               |
+| 0.6481 | 700  | 0.0005        | -               |
+| 0.6944 | 750  | 0.0006        | -               |
+| 0.7407 | 800  | 0.0006        | -               |
+| 0.7870 | 850  | 0.0006        | -               |
+| 0.8333 | 900  | 0.0007        | -               |
+| 0.8796 | 950  | 0.0005        | -               |
+| 0.9259 | 1000 | 0.0004        | -               |
+| 0.9722 | 1050 | 0.0003        | -               |
 
 ### Framework Versions
 - Python: 3.10.12

model.safetensors

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model_head.pkl

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 size 56271