Add SetFit model

README.md

@@ -32,7 +32,7 @@ model-index:
       split: test
     metrics:
     - type: accuracy
-      value: 0.38371040723981903
+      value: 0.4447963800904977
       name: Accuracy
 ---
 
@@ -64,20 +64,20 @@ 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                                                                                                                                                                                                                                                                                                                                              |
-|:------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| 2     | <ul><li>"will no doubt delight plympton 's legion of fans ; others may find 80 minutes of these shenanigans exhausting ."</li><li>"there 's no real reason to see it , and no real reason not to ."</li><li>'in the telling of a story largely untold , bui chooses to produce something that is ultimately suspiciously familiar .'</li></ul>        |
-| 4     | <ul><li>'stevens has a flair for dialogue comedy , the film operates nicely off the element of surprise , and the large cast is solid .'</li><li>'a thought-provoking picture .'</li><li>'arguably the best script that besson has written in years .'</li></ul>                                                                                      |
-| 3     | <ul><li>"trapped presents a frightening and compelling ` what if ? '"</li><li>'cremaster 3 is at once a tough pill to swallow and a minor miracle of self-expression .'</li><li>"toes the fine line between cheese and earnestness remarkably well ; everything is delivered with such conviction that it 's hard not to be carried away ."</li></ul> |
-| 1     | <ul><li>'the laughs are as rare as snake foo yung .'</li><li>'could this be the first major studio production shot on video tape instead of film ?'</li><li>'well , this movie proves you wrong on both counts .'</li></ul>                                                                                                                           |
-| 0     | <ul><li>"... this is n't even a movie we can enjoy as mild escapism ; it is one in which fear and frustration are provoked to intolerable levels ."</li><li>'this kiddie-oriented stinker is so bad that i even caught the gum stuck under my seat trying to sneak out of the theater'</li><li>"as a remake , it 's a pale imitation ."</li></ul>     |
+| Label | Examples                                                                                                                                                                                                                                                                                                                                                                                                                                               |
+|:------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| 2     | <ul><li>"a farce of a parody of a comedy of a premise , it is n't a comparison to reality so much as it is a commentary about our knowledge of films ."</li><li>'mild , meandering teen flick .'</li><li>'wanker goths are on the loose !'</li></ul>                                                                                                                                                                                                   |
+| 4     | <ul><li>"the first tunisian film i have ever seen , and it 's also probably the most good-hearted yet sensual entertainment i 'm likely to see all year ."</li><li>"the film 's intimate camera work and searing performances pull us deep into the girls ' confusion and pain as they struggle tragically to comprehend the chasm of knowledge that 's opened between them ."</li><li>'the film is small in scope , yet perfectly formed .'</li></ul> |
+| 0     | <ul><li>'priggish , lethargically paced parable of renewal .'</li><li>"not at all clear what it 's trying to say and even if it were -- i doubt it would be all that interesting ."</li><li>'an unfortunate title for a film that has nothing endearing about it .'</li></ul>                                                                                                                                                                          |
+| 3     | <ul><li>"you may leave the theater with more questions than answers , but darned if your toes wo n't still be tapping ."</li><li>'an alternately fascinating and frustrating documentary .'</li><li>'instead of hitting the audience over the head with a moral , schrader relies on subtle ironies and visual devices to convey point of view .'</li></ul>                                                                                            |
+| 1     | <ul><li>"it 's not so much a movie as a joint promotion for the national basketball association and teenaged rap and adolescent poster-boy lil ' bow wow ."</li><li>'just the sort of lazy tearjerker that gives movies about ordinary folk a bad name .'</li><li>'well , this movie proves you wrong on both counts .'</li></ul>                                                                                                                      |
 
 ## Evaluation
 
 ### Metrics
 | Label   | Accuracy |
 |:--------|:---------|
-| **all** | 0.3837   |
+| **all** | 0.4448   |
 
 ## Uses
 
@@ -129,7 +129,7 @@ preds = model("my response to the film is best described as lukewarm .")
 ### Training Set Metrics
 | Training set | Min | Median | Max |
 |:-------------|:----|:-------|:----|
-| Word count   | 3   | 16.85  | 34  |
+| Word count   | 2   | 20.45  | 43  |
 
 | Label | Training Sample Count |
 |:------|:----------------------|
@@ -160,11 +160,11 @@ preds = model("my response to the film is best described as lukewarm .")
 ### Training Results
 | Epoch | Step | Training Loss | Validation Loss |
 |:-----:|:----:|:-------------:|:---------------:|
-| 0.005 | 1    | 0.335         | -               |
-| 0.25  | 50   | 0.1776        | -               |
-| 0.5   | 100  | 0.0768        | -               |
-| 0.75  | 150  | 0.0198        | -               |
-| 1.0   | 200  | 0.0072        | -               |
+| 0.005 | 1    | 0.1967        | -               |
+| 0.25  | 50   | 0.0658        | -               |
+| 0.5   | 100  | 0.0883        | -               |
+| 0.75  | 150  | 0.0385        | -               |
+| 1.0   | 200  | 0.0112        | -               |
 
 ### Framework Versions
 - Python: 3.8.10

config_setfit.json

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

model.safetensors

@@ -1,3 +1,3 @@
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model_head.pkl

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