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setfit-quebec-profanity-classifier

Text Classification
setfit
Safetensors
sentence-transformers
xlm-roberta
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Model card Files
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Add SetFit model

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Files changed (4) hide show
  1. README.md +27 -22
  2. config_setfit.json +2 -2
  3. model.safetensors +1 -1
  4. model_head.pkl +1 -1
README.md CHANGED
@@ -60,13 +60,13 @@ The model has been trained using an efficient few-shot learning technique that i
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  - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
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  ### Model Labels
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- | Label | Examples |
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- |:-----------------------------|:--------------------------------------------------------------------------------------------------------------|
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- | sacre composé doux | <ul><li>'Câlique de patente à gosses'</li><li>'Cibole de sapristi de gériboire'</li><li>'eh là là!'</li></ul> |
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- | sacre ponctuation intense | <ul><li>'calvaire'</li><li>'câlisse!'</li><li>'tabarnak!'</li></ul> |
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- | sacre composé intense | <ul><li>'Ciarge de marde'</li><li>'Saint-ciarge de charogne'</li><li>'mosus de bâtard de calvince!'</li></ul> |
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- | "sacre ponctuation intense" | <ul><li>'sti'</li></ul> |
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- | sacre ponctuation doux | <ul><li>'mosus!'</li><li>'tabarouette!'</li><li>'maudit'</li></ul> |
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  ## Evaluation
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@@ -125,7 +125,7 @@ preds = model("esti")
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  ### Training Set Metrics
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  | Training set | Min | Median | Max |
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  |:-------------|:----|:-------|:----|
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- | Word count | 1 | 2.3061 | 6 |
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  | Label | Training Sample Count |
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  |:--------------------------|:----------------------|
@@ -155,20 +155,25 @@ preds = model("esti")
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  ### Training Results
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  | Epoch | Step | Training Loss | Validation Loss |
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  |:-------:|:----:|:-------------:|:---------------:|
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- | 0.0175 | 1 | 0.2319 | - |
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- | 0.8772 | 50 | 0.2153 | 0.0814 |
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- | 1.7544 | 100 | 0.0858 | 0.0042 |
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- | 2.6316 | 150 | 0.002 | 0.0051 |
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- | 3.5088 | 200 | 0.0006 | 0.0058 |
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- | 4.3860 | 250 | 0.0005 | 0.0095 |
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- | 5.2632 | 300 | 0.0003 | 0.0098 |
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- | 6.1404 | 350 | 0.0003 | 0.0103 |
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- | 7.0175 | 400 | 0.0002 | 0.0145 |
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- | 7.8947 | 450 | 0.0002 | 0.0085 |
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- | 8.7719 | 500 | 0.0002 | 0.0114 |
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- | 9.6491 | 550 | 0.0002 | 0.0127 |
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- | 10.5263 | 600 | 0.0002 | 0.0143 |
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- | 11.4035 | 650 | 0.0002 | 0.0148 |
 
 
 
 
 
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  ### Framework Versions
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  - Python: 3.12.10
 
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  - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
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  ### Model Labels
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+ | Label | Examples |
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+ |:-----------------------------|:------------------------------------------------------------------------------------------------------------------------------|
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+ | sacre composé doux | <ul><li>'Saint-cimonaque de sainte-viarge'</li><li>'Cibolac de cibouleau'</li><li>'câline de bines!'</li></ul> |
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+ | sacre ponctuation intense | <ul><li>'sacrament!'</li><li>'siboire!'</li><li>'câlisse!'</li></ul> |
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+ | sacre composé intense | <ul><li>'Ciboire de ciarge'</li><li>"ciboire de viarge de bout d'crisse"</li><li>"sacrement d'tarbarnak de câlisse"</li></ul> |
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+ | sacre ponctuation doux | <ul><li>'tabarouette!'</li><li>'cibole'</li><li>'baptême'</li></ul> |
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+ | "sacre ponctuation intense" | <ul><li>'sti!'</li></ul> |
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  ## Evaluation
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  ### Training Set Metrics
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  | Training set | Min | Median | Max |
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  |:-------------|:----|:-------|:----|
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+ | Word count | 1 | 2.2653 | 6 |
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  | Label | Training Sample Count |
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  |:--------------------------|:----------------------|
 
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  ### Training Results
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  | Epoch | Step | Training Loss | Validation Loss |
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  |:-------:|:----:|:-------------:|:---------------:|
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+ | 0.0175 | 1 | 0.2373 | - |
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+ | 0.8772 | 50 | 0.2157 | 0.0794 |
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+ | 1.7544 | 100 | 0.0818 | 0.0061 |
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+ | 2.6316 | 150 | 0.0014 | 0.0069 |
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+ | 3.5088 | 200 | 0.0004 | 0.0086 |
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+ | 4.3860 | 250 | 0.0003 | 0.0057 |
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+ | 5.2632 | 300 | 0.0003 | 0.0103 |
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+ | 6.1404 | 350 | 0.0002 | 0.0092 |
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+ | 7.0175 | 400 | 0.0002 | 0.0169 |
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+ | 7.8947 | 450 | 0.0002 | 0.0110 |
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+ | 8.7719 | 500 | 0.0002 | 0.0135 |
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+ | 9.6491 | 550 | 0.0002 | 0.0131 |
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+ | 10.5263 | 600 | 0.0001 | 0.0120 |
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+ | 11.4035 | 650 | 0.0001 | 0.0114 |
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+ | 12.2807 | 700 | 0.0001 | 0.0128 |
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+ | 13.1579 | 750 | 0.0001 | 0.0135 |
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+ | 14.0351 | 800 | 0.0001 | 0.0142 |
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+ | 14.9123 | 850 | 0.0001 | 0.0156 |
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+ | 15.7895 | 900 | 0.0001 | 0.0160 |
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  ### Framework Versions
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  - Python: 3.12.10
config_setfit.json CHANGED
@@ -1,9 +1,9 @@
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  {
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- "normalize_embeddings": false,
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  "labels": [
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  "sacre ponctuation intense",
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  "sacre ponctuation doux",
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  "sacre compos\u00e9 intense",
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  "sacre compos\u00e9 doux"
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- ]
 
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  }
 
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  {
 
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  "labels": [
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  "sacre ponctuation intense",
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  "sacre ponctuation doux",
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  "sacre compos\u00e9 intense",
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  "sacre compos\u00e9 doux"
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+ ],
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+ "normalize_embeddings": false
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  }
model.safetensors CHANGED
@@ -1,3 +1,3 @@
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model_head.pkl CHANGED
@@ -1,3 +1,3 @@
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  size 32159
 
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