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setfit_test_imdb

Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
Eval Results
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Add SetFit model

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  1. README.md +44 -54
  2. config.json +1 -1
  3. model.safetensors +1 -1
  4. model_head.pkl +1 -1
README.md CHANGED
@@ -10,38 +10,28 @@ tags:
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  - text-classification
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  - generated_from_setfit_trainer
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  widget:
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- - text: I walked into this movie expecting a thrilling adventure, but what I got was
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- a jumbled mess of characters that made no sense. The main character's personality
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- changed from one scene to the next, it was like they had a different actor playing
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- them. The plot was predictable and the dialogue was cheesy. I left the theater
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- feeling disappointed and frustrated with the wasted potential. The only thing
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- that kept me engaged was the cinematography, but it wasn't enough to save this
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- trainwreck. Overall, I would not recommend this movie to anyone.
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- - text: I recently visited this quaint little cafe and it was love at first sight.
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- The moment I stepped inside, I felt like I was wrapped in a warm hug. The decor
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- is so cozy and inviting, with plush armchairs and soft lighting that makes you
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- feel like you're in a different world. The staff is friendly and attentive, and
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- the coffee is top-notch. I had the most delicious cappuccino and a slice of lemon
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- pound cake that was to die for. I'll definitely be back for more of this cozy
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- ambiance.
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- - text: I just watched the latest Marvel movie and I have to say, it was absolutely
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- phenomenal. The cinematography was breathtaking, the music was catchy and perfectly
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- complemented the on-screen action. The cast delivered outstanding performances,
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- and the storyline was engaging and well-paced. I thoroughly enjoyed every minute
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- of it and would highly recommend it to anyone who loves superhero movies. 10/10
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- would watch again.
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- - text: The movie had so much potential, but the ending was a complete letdown. It
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- felt rushed and didn't provide any closure for the characters. I was expecting
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- a more satisfying conclusion, but what we got was a lazy attempt to tie everything
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- together. The final act was a mess, and it left me feeling frustrated and disappointed.
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- Overall, the movie was enjoyable, but the ending ruined it for me. I would have
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- given it a higher rating if the writers had put more effort into crafting a better
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- ending.
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- - text: The acting in this movie was laughable. The lead actor's delivery was wooden
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- and unconvincing. He had all the charisma of a cardboard box. The supporting cast
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- fared no better, with most of them struggling to deliver even the simplest of
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- lines. The director's attempt to create tension was wasted on the subpar acting,
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- making the entire experience feel like a chore to sit through.
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  inference: true
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  model-index:
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  - name: SetFit with sentence-transformers/paraphrase-mpnet-base-v2
@@ -55,7 +45,7 @@ model-index:
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  split: test
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  metrics:
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  - type: accuracy
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- value: 0.88784
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  name: Accuracy
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  ---
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@@ -87,17 +77,17 @@ 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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- | negative sentiment | <ul><li>'I was really looking forward to this movie, but unfortunately, it was a complete disappointment. The plot was predictable and lacked any real tension. The characters were underdeveloped and their motivations were unclear. The pacing was slow and dragged on for far too long. Overall, I would not recommend this movie to anyone.'</li><li>"I'm extremely disappointed with the service I received at this restaurant. The hostess was unfriendly and unhelpful, and our server seemed completely overwhelmed. We had to ask multiple times for basic things like water and utensils. The food was overpriced and not even that good. Definitely will not be returning."</li><li>"I'm extremely disappointed with my recent purchase from this store. The quality of the product is subpar and the price is way too high. I paid $200 for a cheap-looking item that broke after just a week of use. Not worth the money at all. 1/10 would not recommend."</li></ul> |
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- | positive sentiment | <ul><li>"I just got tickets to see my favorite artist in concert and I'm beyond thrilled! The energy in the crowd is going to be electric! #concertseason #musiclover"</li><li>"I just had the most amazing experience at this restaurant! The service was lightning fast, and the food was prepared to perfection. Our server, Alex, was attentive and friendly, making sure we had everything we needed. The bill was reasonable, and we left feeling satisfied and eager to come back. 5 stars isn't enough, I'd give it 10 if I could!"</li><li>'The action scenes in this movie are absolutely mind-blowing! The stunts are incredibly well-choreographed and the special effects are top-notch. I was on the edge of my seat the entire time, cheering on the heroes as they fought to save the world. The cast is also excellent, with standout performances from the lead actors. Overall, I would highly recommend this movie to anyone who loves action-packed thrill rides.'</li></ul> |
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  ## Evaluation
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  ### Metrics
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  | Label | Accuracy |
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  |:--------|:---------|
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- | **all** | 0.8878 |
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  ## Uses
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@@ -117,7 +107,7 @@ from setfit import SetFitModel
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  # Download from the 🤗 Hub
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  model = SetFitModel.from_pretrained("setfit_model_id")
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  # Run inference
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- preds = model("The acting in this movie was laughable. The lead actor's delivery was wooden and unconvincing. He had all the charisma of a cardboard box. The supporting cast fared no better, with most of them struggling to deliver even the simplest of lines. The director's attempt to create tension was wasted on the subpar acting, making the entire experience feel like a chore to sit through.")
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  ```
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  <!--
@@ -147,14 +137,14 @@ preds = model("The acting in this movie was laughable. The lead actor's delivery
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  ## Training Details
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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 | 23 | 56.8571 | 79 |
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  | Label | Training Sample Count |
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  |:-------------------|:----------------------|
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- | negative sentiment | 14 |
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- | positive sentiment | 14 |
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  ### Training Hyperparameters
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  - batch_size: (16, 16)
@@ -174,16 +164,16 @@ preds = model("The acting in this movie was laughable. The lead actor's delivery
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  - load_best_model_at_end: True
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  ### Training Results
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- | Epoch | Step | Training Loss | Validation Loss |
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- |:-------:|:-------:|:-------------:|:---------------:|
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- | 0.0370 | 1 | 0.2498 | - |
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- | 1.0 | 27 | - | 0.0017 |
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- | 1.8519 | 50 | 0.0003 | - |
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- | 2.0 | 54 | - | 0.0004 |
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- | 3.0 | 81 | - | 0.0003 |
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- | 3.7037 | 100 | 0.0002 | - |
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- | 4.0 | 108 | - | 0.0004 |
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- | **5.0** | **135** | **-** | **0.0003** |
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  * The bold row denotes the saved checkpoint.
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  ### Framework Versions
 
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  - text-classification
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  - generated_from_setfit_trainer
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  widget:
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+ - text: I just watched 'The Shawshank Redemption' and I have to say, Tim Robbins and
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+ Morgan Freeman delivered outstanding performances. Their acting skills truly brought
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+ the characters to life. The way they portrayed the emotional depth of their characters
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+ was impressive. I highly recommend this movie to anyone who loves a good drama.
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+ - text: I walked into this movie expecting a lot, but what I got was a complete waste
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+ of time. The acting was subpar, the plot was predictable, and the dialogue was
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+ cringeworthy. I've seen high school productions that were better. The only thing
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+ that kept me awake was the hope that something, anything, would happen to make
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+ this movie worth watching. Unfortunately, that never came. I would not recommend
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+ this to my worst enemy. 1/10, would not watch again even if you paid me.
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+ - text: I just watched this movie and I'm still grinning from ear to ear. The humor
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+ is wickedly clever and the cast is perfectly assembled. It's a laugh-out-loud
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+ masterpiece that will leave you feeling uplifted and entertained.
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+ - text: I was really looking forward to trying out this new restaurant, but unfortunately,
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+ it was a huge disappointment. The service was slow, the food was cold, and the
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+ ambiance was non-existent. I ordered the burger, but it was overcooked and tasted
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+ like it had been sitting out for hours. Needless to say, I won't be back.
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+ - text: I recently visited this restaurant for lunch and had an amazing experience.
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+ The service was top-notch, our server was friendly and attentive, and the food
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+ was incredible. I ordered the grilled chicken salad and it was cooked to perfection.
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+ The portion size was generous and the prices were very reasonable. I would highly
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+ recommend this place to anyone looking for a great meal.
 
 
 
 
 
 
 
 
 
 
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  inference: true
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  model-index:
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  - name: SetFit with sentence-transformers/paraphrase-mpnet-base-v2
 
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  split: test
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  metrics:
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  - type: accuracy
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+ value: 0.87812
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  name: Accuracy
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  ---
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  - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
78
 
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  ### Model Labels
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+ | Label | Examples |
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+ |:-------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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+ | positive sentiment | <ul><li>"I just watched the latest Marvel movie and I'm still reeling from the shocking plot twist at the end. I didn't see it coming and it completely flipped my expectations on their head. The way the story unfolded was pure genius and had me on the edge of my seat the entire time. I'm not even kidding when I say that this movie is a must-see for anyone who loves a good surprise. 10/10 would recommend."</li><li>'I recently visited this restaurant and was blown away by the exceptional service from the staff. Our server, Alex, was attentive, knowledgeable, and made sure we had everything we needed throughout our meal. The food was delicious, but the service was truly what made our experience stand out. I would highly recommend this place to anyone looking for a great dining experience.'</li><li>"I just watched the funniest movie of my life, 'Dumb and Dumber'! Jim Carrey's comedic timing is unmatched. He has this incredible ability to make you laugh without even trying. The movie is full of hilarious moments, and I found myself giggling uncontrollably throughout. I highly recommend it to anyone looking for a good laugh."</li></ul> |
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+ | negative sentiment | <ul><li>"I'm extremely disappointed with my recent purchase from this restaurant. The food was overcooked and the service was slow. The prices are way too high for the quality of food you receive. I won't be returning anytime soon."</li><li>"I'm extremely disappointed with the service I received at this restaurant. The hostess was completely unfriendly and unhelpful. We were seated for 20 minutes before anyone even came to take our order. The food was overpriced and took an hour to arrive. The server seemed put off by our presence and didn't even bother to refill our drinks. Needless to say, we will never be back."</li><li>'I was really looking forward to this movie, but unfortunately, it fell flat. The plot was predictable and lacked any real tension or suspense. The characters were underdeveloped and their motivations were unclear. The pacing was slow and the ending was completely unsatisfying. Overall, I was disappointed by the lack of effort put into creating a compelling story. 1/10 would not recommend.'</li></ul> |
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  ## Evaluation
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  ### Metrics
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  | Label | Accuracy |
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  |:--------|:---------|
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+ | **all** | 0.8781 |
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  ## Uses
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107
  # Download from the 🤗 Hub
108
  model = SetFitModel.from_pretrained("setfit_model_id")
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  # Run inference
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+ preds = model("I just watched this movie and I'm still grinning from ear to ear. The humor is wickedly clever and the cast is perfectly assembled. It's a laugh-out-loud masterpiece that will leave you feeling uplifted and entertained.")
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  ```
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  <!--
 
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  ## Training Details
138
 
139
  ### Training Set Metrics
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+ | Training set | Min | Median | Max |
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+ |:-------------|:----|:-------|:----|
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+ | Word count | 20 | 50.76 | 80 |
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  | Label | Training Sample Count |
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  |:-------------------|:----------------------|
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+ | negative sentiment | 13 |
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+ | positive sentiment | 12 |
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  ### Training Hyperparameters
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  - batch_size: (16, 16)
 
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  - load_best_model_at_end: True
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  ### Training Results
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+ | Epoch | Step | Training Loss | Validation Loss |
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+ |:-------:|:------:|:-------------:|:---------------:|
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+ | 0.0455 | 1 | 0.1789 | - |
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+ | 1.0 | 22 | - | 0.013 |
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+ | 2.0 | 44 | - | 0.0024 |
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+ | 2.2727 | 50 | 0.0003 | - |
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+ | 3.0 | 66 | - | 0.0014 |
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+ | **4.0** | **88** | **-** | **0.0011** |
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+ | 4.5455 | 100 | 0.0003 | - |
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+ | 5.0 | 110 | - | 0.0013 |
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  * The bold row denotes the saved checkpoint.
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  ### Framework Versions
config.json CHANGED
@@ -1,5 +1,5 @@
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  {
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- "_name_or_path": "setfit/step_135",
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  "architectures": [
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  "MPNetModel"
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  ],
 
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  {
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+ "_name_or_path": "setfit/step_88",
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  "architectures": [
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  "MPNetModel"
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  ],
model.safetensors CHANGED
@@ -1,3 +1,3 @@
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  size 437967672
 
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model_head.pkl CHANGED
@@ -1,3 +1,3 @@
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