Push model using huggingface_hub.

1_Pooling/config.json

@@ -0,0 +1,10 @@
+{
+  "word_embedding_dimension": 384,
+  "pooling_mode_cls_token": true,
+  "pooling_mode_mean_tokens": false,
+  "pooling_mode_max_tokens": false,
+  "pooling_mode_mean_sqrt_len_tokens": false,
+  "pooling_mode_weightedmean_tokens": false,
+  "pooling_mode_lasttoken": false,
+  "include_prompt": true
+}

README.md

@@ -5,22 +5,21 @@ tags:
 - sentence-transformers
 - text-classification
 - generated_from_setfit_trainer
+base_model: BAAI/bge-small-en-v1.5
 metrics:
 - accuracy
 widget:
-- text: amy and matthew have a bit of a phony relationship , but the film works in
-    spite of it .
-- text: it 's refreshing to see a romance this smart .
-- text: bogdanich is unashamedly pro-serbian and makes little attempt to give voice
-    to the other side .
-- text: sayles has an eye for the ways people of different ethnicities talk to and
-    about others outside the group .
-- text: eddie murphy and owen wilson have a cute partnership in i spy , but the movie
-    around them is so often nearly nothing that their charm does n't do a load of
-    good .
+- text: mostly works because of the universal themes , earnest performances ... and
+    excellent use of music by india 's popular gulzar and jagjit singh .
+- text: in all the annals of the movies , few films have been this odd , inexplicable
+    and unpleasant .
+- text: director charles stone iii applies more detail to the film 's music than to
+    the story line ; what 's best about drumline is its energy .
+- text: there 's nothing exactly wrong here , but there 's not nearly enough that
+    's right .
+- text: it 's a bad sign in a thriller when you instantly know whodunit .
 pipeline_tag: text-classification
 inference: true
-base_model: BAAI/bge-small-en-v1.5
 model-index:
 - name: SetFit with BAAI/bge-small-en-v1.5
   results:
@@ -33,9 +32,10 @@ model-index:
       split: test
     metrics:
     - type: accuracy
-      value: 0.8478857770455793
+      value: 0.8621636463481603
       name: Accuracy
 ---
+
 # SetFit with BAAI/bge-small-en-v1.5
 
 This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) 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.
@@ -64,17 +64,17 @@ The model has been trained using an efficient few-shot learning technique that i
 - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
 
 ### Model Labels
-| Label    | Examples                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
-|:---------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| negative | <ul><li>'there might be some sort of credible gender-provoking philosophy submerged here , but who the hell cares ?'</li><li>'represents the depths to which the girls-behaving-badly film has fallen .'</li><li>'-lrb- a -rrb- crushing disappointment .'</li></ul>                                                                                                                                                                                                                                                |
-| positive | <ul><li>'what saves it ... and makes it one of the better video-game-based flicks , is that the film acknowledges upfront that the plot makes no sense , such that the lack of linearity is the point of emotional and moral departure for protagonist alice .'</li><li>'but it could be , by its art and heart , a necessary one .'</li><li>'a culture-clash comedy that , in addition to being very funny , captures some of the discomfort and embarrassment of being a bumbling american in europe .'</li></ul> |
+| Label | Examples                                                                                                                                                                                                                                                                                                                                                                                                                      |
+|:------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| 1     | <ul><li>'a sensitive , modest comic tragedy that works as both character study and symbolic examination of the huge economic changes sweeping modern china .'</li><li>'the year 2002 has conjured up more coming-of-age stories than seem possible , but take care of my cat emerges as the very best of them .'</li><li>'amy and matthew have a bit of a phony relationship , but the film works in spite of it .'</li></ul> |
+| 0     | <ul><li>'works on the whodunit level as its larger themes get lost in the murk of its own making'</li><li>"one of those strained caper movies that 's hardly any fun to watch and begins to vaporize from your memory minutes after it ends ."</li><li>"shunji iwai 's all about lily chou chou is a beautifully shot , but ultimately flawed film about growing up in japan ."</li></ul>                                     |
 
 ## Evaluation
 
 ### Metrics
 | Label   | Accuracy |
 |:--------|:---------|
-| **all** |  0.862   |
+| **all** | 0.8622   |
 
 ## Uses
 
@@ -90,10 +90,11 @@ Then you can load this model and run inference.
 
 ```python
 from setfit import SetFitModel
+
 # Download from the 🤗 Hub
 model = SetFitModel.from_pretrained("Jorgeutd/setfit-bge-small-v1.5-sst2-50-shot")
 # Run inference
-preds = model("it 's refreshing to see a romance this smart .")
+preds = model("it 's a bad sign in a thriller when you instantly know whodunit .")
 ```
 
 <!--
@@ -125,12 +126,12 @@ preds = model("it 's refreshing to see a romance this smart .")
 ### Training Set Metrics
 | Training set | Min | Median | Max |
 |:-------------|:----|:-------|:----|
-| Word count   | 6   | 22.5   | 45  |
+| Word count   | 3   | 21.31  | 50  |
 
-| Label    | Training Sample Count |
-|:---------|:----------------------|
-| negative | 50                     |
-| positive | 50                     |
+| Label | Training Sample Count |
+|:------|:----------------------|
+| 0     | 50                    |
+| 1     | 50                    |
 
 ### Training Hyperparameters
 - batch_size: (16, 16)
@@ -150,19 +151,81 @@ preds = model("it 's refreshing to see a romance this smart .")
 - load_best_model_at_end: False
 
 ### Training Results
-| Epoch | Step | Training Loss | Validation Loss |
-|:-----:|:----:|:-------------:|:---------------:|
-| 0.2   | 1    | 0.2109        | -               |
-| 10.0  | 50   | 0.01          | -               |
+| Epoch  | Step | Training Loss | Validation Loss |
+|:------:|:----:|:-------------:|:---------------:|
+| 0.0031 | 1    | 0.2515        | -               |
+| 0.1567 | 50   | 0.2298        | -               |
+| 0.3135 | 100  | 0.2134        | -               |
+| 0.4702 | 150  | 0.0153        | -               |
+| 0.6270 | 200  | 0.0048        | -               |
+| 0.7837 | 250  | 0.0024        | -               |
+| 0.9404 | 300  | 0.0023        | -               |
+| 1.0972 | 350  | 0.0016        | -               |
+| 1.2539 | 400  | 0.0016        | -               |
+| 1.4107 | 450  | 0.001         | -               |
+| 1.5674 | 500  | 0.0013        | -               |
+| 1.7241 | 550  | 0.0008        | -               |
+| 1.8809 | 600  | 0.0008        | -               |
+| 2.0376 | 650  | 0.0007        | -               |
+| 2.1944 | 700  | 0.0008        | -               |
+| 2.3511 | 750  | 0.0008        | -               |
+| 2.5078 | 800  | 0.0007        | -               |
+| 2.6646 | 850  | 0.0006        | -               |
+| 2.8213 | 900  | 0.0006        | -               |
+| 2.9781 | 950  | 0.0005        | -               |
+| 3.1348 | 1000 | 0.0006        | -               |
+| 3.2915 | 1050 | 0.0006        | -               |
+| 3.4483 | 1100 | 0.0005        | -               |
+| 3.6050 | 1150 | 0.0005        | -               |
+| 3.7618 | 1200 | 0.0005        | -               |
+| 3.9185 | 1250 | 0.0005        | -               |
+| 4.0752 | 1300 | 0.0005        | -               |
+| 4.2320 | 1350 | 0.0004        | -               |
+| 4.3887 | 1400 | 0.0004        | -               |
+| 4.5455 | 1450 | 0.0004        | -               |
+| 4.7022 | 1500 | 0.0003        | -               |
+| 4.8589 | 1550 | 0.0006        | -               |
+| 5.0157 | 1600 | 0.0007        | -               |
+| 5.1724 | 1650 | 0.0004        | -               |
+| 5.3292 | 1700 | 0.0004        | -               |
+| 5.4859 | 1750 | 0.0004        | -               |
+| 5.6426 | 1800 | 0.0004        | -               |
+| 5.7994 | 1850 | 0.0003        | -               |
+| 5.9561 | 1900 | 0.0004        | -               |
+| 6.1129 | 1950 | 0.0003        | -               |
+| 6.2696 | 2000 | 0.0003        | -               |
+| 6.4263 | 2050 | 0.0005        | -               |
+| 6.5831 | 2100 | 0.0003        | -               |
+| 6.7398 | 2150 | 0.0003        | -               |
+| 6.8966 | 2200 | 0.0003        | -               |
+| 7.0533 | 2250 | 0.0003        | -               |
+| 7.2100 | 2300 | 0.0003        | -               |
+| 7.3668 | 2350 | 0.0003        | -               |
+| 7.5235 | 2400 | 0.0002        | -               |
+| 7.6803 | 2450 | 0.0003        | -               |
+| 7.8370 | 2500 | 0.0003        | -               |
+| 7.9937 | 2550 | 0.0003        | -               |
+| 8.1505 | 2600 | 0.0003        | -               |
+| 8.3072 | 2650 | 0.0003        | -               |
+| 8.4639 | 2700 | 0.0003        | -               |
+| 8.6207 | 2750 | 0.0003        | -               |
+| 8.7774 | 2800 | 0.0004        | -               |
+| 8.9342 | 2850 | 0.0002        | -               |
+| 9.0909 | 2900 | 0.0003        | -               |
+| 9.2476 | 2950 | 0.0004        | -               |
+| 9.4044 | 3000 | 0.0004        | -               |
+| 9.5611 | 3050 | 0.0003        | -               |
+| 9.7179 | 3100 | 0.0004        | -               |
+| 9.8746 | 3150 | 0.0003        | -               |
 
 ### Framework Versions
-- Python: 3.10.11
+- Python: 3.10.13
 - SetFit: 1.0.3
-- Sentence Transformers: 2.3.1
-- Transformers: 4.37.2
-- PyTorch: 2.2.0+cu121
-- Datasets: 2.16.1
-- Tokenizers: 0.15.1
+- Sentence Transformers: 2.6.1
+- Transformers: 4.39.1
+- PyTorch: 2.1.0
+- Datasets: 2.18.0
+- Tokenizers: 0.15.2
 
 ## Citation
 
@@ -179,6 +242,21 @@ preds = model("it 's refreshing to see a romance this smart .")
     copyright = {Creative Commons Attribution 4.0 International}
 }
 ```
----
-license: apache-2.0
----
+
+<!--
+## Glossary
+
+*Clearly define terms in order to be accessible across audiences.*
+-->
+
+<!--
+## Model Card Authors
+
+*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
+-->
+
+<!--
+## Model Card Contact
+
+*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
+-->

config.json

@@ -0,0 +1,31 @@
+{
+  "_name_or_path": "BAAI/bge-small-en-v1.5",
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 384,
+  "id2label": {
+    "0": "LABEL_0"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "label2id": {
+    "LABEL_0": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.39.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

config_sentence_transformers.json

@@ -0,0 +1,9 @@
+{
+  "__version__": {
+    "sentence_transformers": "2.2.2",
+    "transformers": "4.28.1",
+    "pytorch": "1.13.0+cu117"
+  },
+  "prompts": {},
+  "default_prompt_name": null
+}

config_setfit.json

@@ -0,0 +1,4 @@
+{
+  "normalize_embeddings": false,
+  "labels": null
+}

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4ed5ae86db9742447235984fb83c57b4660ebce9c29d81901fa05b1a37d8deeb
+size 133462128

model_head.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8365e74dece1c00a9d150d662c5584ee6b7ecd3fb05c047095d7d40e2286a06a
+size 3941

modules.json

@@ -0,0 +1,20 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  },
+  {
+    "idx": 2,
+    "name": "2",
+    "path": "2_Normalize",
+    "type": "sentence_transformers.models.Normalize"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+  "max_seq_length": 512,
+  "do_lower_case": true
+}

special_tokens_map.json

@@ -0,0 +1,37 @@
+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "[PAD]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "[SEP]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,57 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}