Add SetFit model

README.md

@@ -1,15 +1,6 @@
 ---
-base_model: BAAI/bge-small-en-v1.5
 language: en
-library_name: setfit
 license: apache-2.0
-metrics:
-- '0'
-- '1'
-- accuracy
-- macro avg
-- weighted avg
-pipeline_tag: text-classification
 tags:
 - setfit
 - sentence-transformers
@@ -21,7 +12,16 @@ widget:
 - text: Obesity can cause resistance to which hormone?
 - text: Referees
 - text: where does the water at niagra falls come from
+metrics:
+- '0'
+- '1'
+- accuracy
+- macro avg
+- weighted avg
+pipeline_tag: text-classification
+library_name: setfit
 inference: true
+base_model: BAAI/bge-small-en-v1.5
 model-index:
 - name: SetFit with BAAI/bge-small-en-v1.5 on Health Information Needs
   results:
@@ -35,33 +35,33 @@ model-index:
     metrics:
     - type: '0'
       value:
-        precision: 0.36527485731450887
-        recall: 0.990228013029316
-        f1-score: 0.5336844415185429
+        precision: 0.37465309898242366
+        recall: 0.989413680781759
+        f1-score: 0.5435025721315142
         support: 1228.0
       name: '0'
     - type: '1'
       value:
-        precision: 0.994328922495274
-        recall: 0.4989328906805786
-        f1-score: 0.6644560240012632
+        precision: 0.9940962761126249
+        recall: 0.5190894000474271
+        f1-score: 0.6820377005764138
         support: 4217.0
       name: '1'
     - type: accuracy
-      value: 0.6097337006427915
+      value: 0.6251606978879706
       name: Accuracy
     - type: macro avg
       value:
-        precision: 0.6798018899048914
-        recall: 0.7445804518549473
-        f1-score: 0.5990702327599031
+        precision: 0.6843746875475243
+        recall: 0.7542515404145931
+        f1-score: 0.6127701363539639
         support: 5445.0
       name: Macro Avg
     - type: weighted avg
       value:
-        precision: 0.8524596126620364
-        recall: 0.6097337006427915
-        f1-score: 0.6349633695864275
+        precision: 0.8543944907102582
+        recall: 0.6251606978879706
+        f1-score: 0.6507941491107871
         support: 5445.0
       name: Weighted Avg
 ---
@@ -102,9 +102,9 @@ The model has been trained using an efficient few-shot learning technique that i
 ## Evaluation
 
 ### Metrics
-| Label   | 0                                                                                                                  | 1                                                                                                                 | Accuracy | Macro Avg                                                                                                          | Weighted Avg                                                                                                       |
-|:--------|:-------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------|:---------|:-------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------|
-| **all** | {'precision': 0.36527485731450887, 'recall': 0.990228013029316, 'f1-score': 0.5336844415185429, 'support': 1228.0} | {'precision': 0.994328922495274, 'recall': 0.4989328906805786, 'f1-score': 0.6644560240012632, 'support': 4217.0} | 0.6097   | {'precision': 0.6798018899048914, 'recall': 0.7445804518549473, 'f1-score': 0.5990702327599031, 'support': 5445.0} | {'precision': 0.8524596126620364, 'recall': 0.6097337006427915, 'f1-score': 0.6349633695864275, 'support': 5445.0} |
+| Label   | 0                                                                                                                  | 1                                                                                                                  | Accuracy | Macro Avg                                                                                                          | Weighted Avg                                                                                                       |
+|:--------|:-------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------|:---------|:-------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------|
+| **all** | {'precision': 0.37465309898242366, 'recall': 0.989413680781759, 'f1-score': 0.5435025721315142, 'support': 1228.0} | {'precision': 0.9940962761126249, 'recall': 0.5190894000474271, 'f1-score': 0.6820377005764138, 'support': 4217.0} | 0.6252   | {'precision': 0.6843746875475243, 'recall': 0.7542515404145931, 'f1-score': 0.6127701363539639, 'support': 5445.0} | {'precision': 0.8543944907102582, 'recall': 0.6251606978879706, 'f1-score': 0.6507941491107871, 'support': 5445.0} |
 
 ## Uses
 
@@ -122,7 +122,7 @@ Then you can load this model and run inference.
 from setfit import SetFitModel
 
 # Download from the 🤗 Hub
-model = SetFitModel.from_pretrained("setfit_model_id")
+model = SetFitModel.from_pretrained("fuhakiem/hin-v001-trainer")
 # Run inference
 preds = model("Referees")
 ```
@@ -184,16 +184,16 @@ preds = model("Referees")
 ### Training Results
 | Epoch | Step | Training Loss | Validation Loss |
 |:-----:|:----:|:-------------:|:---------------:|
-| 0.5   | 1    | 0.1884        | -               |
+| 0.5   | 1    | 0.1957        | -               |
 
 ### Framework Versions
-- Python: 3.12.2
+- Python: 3.10.12
 - SetFit: 1.1.0
-- Sentence Transformers: 3.0.1
-- Transformers: 4.45.2
-- PyTorch: 2.2.2
-- Datasets: 3.1.0
-- Tokenizers: 0.20.3
+- Sentence Transformers: 3.3.1
+- Transformers: 4.42.2
+- PyTorch: 2.5.1+cu124
+- Datasets: 3.2.0
+- Tokenizers: 0.19.1
 
 ## Citation
 

config.json

@@ -24,7 +24,7 @@
   "pad_token_id": 0,
   "position_embedding_type": "absolute",
   "torch_dtype": "float32",
-  "transformers_version": "4.45.2",
+  "transformers_version": "4.42.2",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 30522

config_sentence_transformers.json

@@ -1,10 +1,10 @@
 {
   "__version__": {
-    "sentence_transformers": "3.0.1",
-    "transformers": "4.45.2",
-    "pytorch": "2.2.2"
+    "sentence_transformers": "3.3.1",
+    "transformers": "4.42.2",
+    "pytorch": "2.5.1+cu124"
   },
   "prompts": {},
   "default_prompt_name": null,
-  "similarity_fn_name": null
+  "similarity_fn_name": "cosine"
 }

config_setfit.json

@@ -1,4 +1,4 @@
 {
-  "labels": null,
-  "normalize_embeddings": false
+  "normalize_embeddings": false,
+  "labels": null
 }

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:486ea20f55ffb50896c78a545f8ca61471c6d8a206cfa10f5fdfe3af6eb95c79
+oid sha256:59a6f525290b965ac5ae9a927008897b42fddab2cec689248a2dbc043985d8c7
 size 133462128

model_head.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8f9cc29255d2c9868230092de6a5de0a30183110524ea434529c78c21306ea6f
+oid sha256:bd9c39ca5b3bebc9d2296e5335d570a913e082436e698e6e9f291ad18449b21a
 size 3935