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JordanTallon
/
Unifeed

Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
Eval Results
Model card Files Community
JordanTallon commited on
Commit
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  1. README.md +223 -91
  2. model.safetensors +1 -1
  3. model_head.pkl +1 -1
README.md CHANGED
@@ -6,23 +6,27 @@ tags:
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  - text-classification
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  - generated_from_setfit_trainer
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  metrics:
 
 
 
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  - accuracy
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  widget:
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- - text: The ban, which went into effect in March 2019, was embraced by Trump following
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- a massacre that killed 58 people at a music festival in Las Vegas in which the
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- gunman used bump stocks.
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- - text: 'Now Modi has made international headlines for yet another similarity: He’s
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- constructing a massive wall … but unlike Trump’s goal of keeping immigrants out,
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- Modi’s wall was built to hide the country’s poverty from the gold-plated American
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- president.'
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- - text: 'Though banks have fled many low-income communities, there’s a post office
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- for almost every ZIP code in the country. '
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- - text: The administration has stonewalled Congress during the impeachment proceedings
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- and other investigations, but the American public overwhelmingly wants the Trump
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- administration to comply with lawmakers.
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- - text: The gun lobby has repeatedly claimed that using a gun in self-defense is a
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- common event, often going so far as to allege that Americans defend themselves
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- with guns millions of times a year.
 
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  pipeline_tag: text-classification
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  inference: true
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  base_model: BAAI/bge-small-en-v1.5
@@ -37,8 +41,17 @@ model-index:
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  type: unknown
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  split: test
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  metrics:
 
 
 
 
 
 
 
 
 
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  - type: accuracy
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- value: 0.67003367003367
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  name: Accuracy
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  ---
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@@ -70,18 +83,18 @@ 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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72
  ### Model Labels
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- | Label | Examples |
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- |:-------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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- | center | <ul><li>'A leading economist who vouched for Democratic presidential candidate Elizabeth Warren’s healthcare reform plan told Reuters on Thursday he doubts its staggering cost can be fully covered alongside her other government programs.'</li><li>'Labour leader Jeremy Corbyn unveiled his party’s election manifesto on Thursday, setting out radical plans to transform Britain with public sector pay rises, higher taxes on companies and a sweeping nationalisation of infrastructure.'</li><li>'Instagram will start blocking any hashtags spreading misinformation about vaccines, becoming the latest internet platform to crack down on bad health information.'</li></ul> |
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- | right | <ul><li>'Sanders praises the radical Green New Deal, champions a Medicare for All plan with a $34 trillion price tag, nods to abortion as a means of population control, and defends bread lines and Fidel Castro’s Cuba. '</li><li>'Since when did even conservative publications consider that it’s the right and moral thing to do to provide covering fire for an increasingly thuggish, openly hard-left, and borderline terroristic group which is less obviously to do with ‘racism’, but which has almost everything to do with smashing Western civilisation?'</li><li>'Local health officer\xa0Dr Rosana Salvaterra appeared to co-sign the demonstration,\xa0praising activists\xa0for wearing masks and claiming they obeyed social distancing protocols — although\xa0footage\xa0of the event strongly suggests that is\xa0not strictly accurate.'</li></ul> |
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- | left | <ul><li>'Activists planning to line California roadways with anti-vaccination billboards full of misinformation are paying for them through Facebook fundraisers, despite a platform-wide crackdown on such campaigns.'</li><li>'On Monday, as\xa0Common Dreams\xa0reported, Trump threatened to deploy federal forces to Chicago, Philadelphia, Detroit, Baltimore, and Oakland to confront Black Lives Matter protesters.'</li><li>"When the nation's highest civilian honor went to a right-wing media personality, it served as an oddly appropriate capstone to Trump's broader goals."</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** | 0.6700 |
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  ## Uses
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@@ -101,7 +114,7 @@ from setfit import SetFitModel
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  # Download from the 🤗 Hub
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  model = SetFitModel.from_pretrained("JordanTallon/Unifeed")
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  # Run inference
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- preds = model("Though banks have fled many low-income communities, there’s a post office for almost every ZIP code in the country. ")
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  ```
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107
  <!--
@@ -133,17 +146,17 @@ preds = model("Though banks have fled many low-income communities, there’s a p
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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 | 33.0139 | 195 |
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  | Label | Training Sample Count |
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  |:-------|:----------------------|
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- | center | 782 |
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- | left | 780 |
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- | right | 813 |
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  ### Training Hyperparameters
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- - batch_size: (64, 64)
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- - num_epochs: (2, 2)
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  - max_steps: -1
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  - sampling_strategy: oversampling
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  - num_iterations: 20
@@ -162,66 +175,185 @@ preds = model("Though banks have fled many low-income communities, there’s a p
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  ### Training Results
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  | Epoch | Step | Training Loss | Validation Loss |
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  |:------:|:----:|:-------------:|:---------------:|
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- | 0.0007 | 1 | 0.2531 | - |
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- | 0.0337 | 50 | 0.253 | - |
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- | 0.0673 | 100 | 0.2491 | - |
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- | 0.1010 | 150 | 0.2592 | - |
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- | 0.1347 | 200 | 0.2476 | - |
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- | 0.1684 | 250 | 0.2282 | - |
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- | 0.2020 | 300 | 0.2222 | - |
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- | 0.2357 | 350 | 0.2196 | - |
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- | 0.2694 | 400 | 0.2199 | - |
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- | 0.3030 | 450 | 0.1821 | - |
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- | 0.3367 | 500 | 0.1819 | - |
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- | 0.3704 | 550 | 0.1327 | - |
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- | 0.4040 | 600 | 0.1193 | - |
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- | 0.4377 | 650 | 0.1652 | - |
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- | 0.4714 | 700 | 0.1059 | - |
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- | 0.5051 | 750 | 0.1141 | - |
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- | 0.5387 | 800 | 0.1103 | - |
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- | 0.5724 | 850 | 0.1138 | - |
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- | 0.6061 | 900 | 0.0894 | - |
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- | 0.6397 | 950 | 0.1138 | - |
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- | 0.6734 | 1000 | 0.11 | - |
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- | 0.7071 | 1050 | 0.1091 | - |
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- | 0.7407 | 1100 | 0.0804 | - |
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- | 0.7744 | 1150 | 0.1161 | - |
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- | 0.8081 | 1200 | 0.0715 | - |
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- | 0.8418 | 1250 | 0.1 | - |
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- | 0.8754 | 1300 | 0.0687 | - |
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- | 0.9091 | 1350 | 0.0488 | - |
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- | 0.9428 | 1400 | 0.0354 | - |
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- | 0.9764 | 1450 | 0.0244 | - |
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- | 1.0101 | 1500 | 0.02 | - |
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- | 1.0438 | 1550 | 0.0179 | - |
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- | 1.0774 | 1600 | 0.0219 | - |
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- | 1.1111 | 1650 | 0.0056 | - |
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- | 1.1448 | 1700 | 0.0169 | - |
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- | 1.1785 | 1750 | 0.0038 | - |
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- | 1.2121 | 1800 | 0.0139 | - |
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- | 1.2458 | 1850 | 0.0154 | - |
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- | 1.2795 | 1900 | 0.0118 | - |
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- | 1.3131 | 1950 | 0.0019 | - |
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- | 1.3468 | 2000 | 0.0016 | - |
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- | 1.3805 | 2050 | 0.0019 | - |
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- | 1.4141 | 2100 | 0.0016 | - |
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- | 1.4478 | 2150 | 0.0017 | - |
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- | 1.4815 | 2200 | 0.0011 | - |
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- | 1.5152 | 2250 | 0.0013 | - |
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- | 1.5488 | 2300 | 0.0123 | - |
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- | 1.5825 | 2350 | 0.0014 | - |
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- | 1.6162 | 2400 | 0.0013 | - |
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- | 1.6498 | 2450 | 0.001 | - |
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- | 1.6835 | 2500 | 0.0042 | - |
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- | 1.7172 | 2550 | 0.0017 | - |
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- | 1.7508 | 2600 | 0.0027 | - |
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- | 1.7845 | 2650 | 0.0016 | - |
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- | 1.8182 | 2700 | 0.0011 | - |
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- | 1.8519 | 2750 | 0.0014 | - |
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- | 1.8855 | 2800 | 0.0012 | - |
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- | 1.9192 | 2850 | 0.0012 | - |
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- | 1.9529 | 2900 | 0.0009 | - |
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- | 1.9865 | 2950 | 0.001 | - |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework Versions
227
  - Python: 3.10.12
 
6
  - text-classification
7
  - generated_from_setfit_trainer
8
  metrics:
9
+ - f1
10
+ - precision
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+ - recall
12
  - accuracy
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  widget:
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+ - text: Since the start of the coronavirus outbreak, Trump has hampered efforts to
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+ slow the virus’s spread and encouraged Americans’ restlessness under quarantine.
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+ - text: ' It has to be particularly described what he is looking for said Asha Rangappa
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+ who was a counter intelligence agent for the FBI and now a Yale Law School professor
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+ A judge isn t going to sign off some sort of blanket warrant that tells Facebook
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+ to turn over everything '
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+ - text: 'Now in response to these very serious crises it seems to me that we have
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+ two choices First we can throw up our hands in despair We can say I am not going
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+ to get involved '
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+ - text: Over the past week, activists, some of who are believed to be affiliated with
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+ Black Lives Matter have rioted across the country following the death of George
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+ Floyd in police custody, wreaking havoc and destruction against America’s towns,
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+ cities, and local communities. 
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+ - text: Working-class Americans, like those who make up the majority of South Bend
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+ residents, have secured the largest wage hikes in the nation compared to all other
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+ economic demographic groups — a direct result of Trump tightening the labor market.
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  pipeline_tag: text-classification
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  inference: true
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  base_model: BAAI/bge-small-en-v1.5
 
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  type: unknown
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  split: test
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  metrics:
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+ - type: f1
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+ value: 0.6952861952861953
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+ name: F1
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+ - type: precision
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+ value: 0.6952861952861953
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+ name: Precision
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+ - type: recall
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+ value: 0.6952861952861953
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+ name: Recall
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  - type: accuracy
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+ value: 0.6952861952861953
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  name: Accuracy
56
  ---
57
 
 
83
  - **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
84
 
85
  ### Model Labels
86
+ | Label | Examples |
87
+ |:-------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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+ | center | <ul><li>'A leading economist who vouched for Democratic presidential candidate Elizabeth Warren’s healthcare reform plan told Reuters on Thursday he doubts its staggering cost can be fully covered alongside her other government programs.'</li><li>'U.S. President Donald Trump is doing well and is very healthy, White House adviser Kellyanne Conway told Fox News on Thursday, after a U.S. military official who worked at the White House was found to have been infected with the novel coronavirus.'</li><li>'Alabama has the most restrictive abortion law in the U.S., banning abortion at any stage of pregnancy and for any reason, including in cases of rape and incest.'</li></ul> |
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+ | left | <ul><li>'Meet the shadowy accountants who do Trump’s taxes and help him seem richer than he is'</li><li>'When did vaccines become politicized? Amid a measles outbreak, suddenly Republicans support anti-vaxxers.'</li><li>'Last summer, the Republican White House announced plans to roll back the tougher standards, making it easier for the automotive industry to sell less efficient vehicles that pollute more.'</li></ul> |
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+ | right | <ul><li>'Joe Biden told Wall Street donors to his campaign that he planned to reverse most of President Donald Trump’s tax cuts.'</li><li>'For far too many on the left, chaos is the point. Destruction is the goal. They prefer the unknown madness that lies ahead to whatever is still managing to (barely) hold us together in the present.'</li><li>'Cuba’s health ministry initially vowed an investigation into Paloma Dominguez Caballero’s death; last week, state media published a report essentially absolving the government of any wrongdoing, categorically stating that nothing was wrong with the vaccine Dominguez received.'</li></ul> |
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92
  ## Evaluation
93
 
94
  ### Metrics
95
+ | Label | F1 | Precision | Recall | Accuracy |
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+ |:--------|:-------|:----------|:-------|:---------|
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+ | **all** | 0.6953 | 0.6953 | 0.6953 | 0.6953 |
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99
  ## Uses
100
 
 
114
  # Download from the 🤗 Hub
115
  model = SetFitModel.from_pretrained("JordanTallon/Unifeed")
116
  # Run inference
117
+ preds = model("Since the start of the coronavirus outbreak, Trump has hampered efforts to slow the virus’s spread and encouraged Americans’ restlessness under quarantine.")
118
  ```
119
 
120
  <!--
 
146
  ### Training Set Metrics
147
  | Training set | Min | Median | Max |
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  |:-------------|:----|:--------|:----|
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+ | Word count | 6 | 33.1655 | 86 |
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  | Label | Training Sample Count |
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  |:-------|:----------------------|
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+ | center | 802 |
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+ | left | 784 |
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+ | right | 788 |
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  ### Training Hyperparameters
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+ - batch_size: (32, 32)
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+ - num_epochs: (3, 3)
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  - max_steps: -1
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  - sampling_strategy: oversampling
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  - num_iterations: 20
 
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  ### Training Results
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  | Epoch | Step | Training Loss | Validation Loss |
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  |:------:|:----:|:-------------:|:---------------:|
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+ | 0.0003 | 1 | 0.2552 | - |
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+ | 0.0168 | 50 | 0.2613 | - |
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+ | 0.0337 | 100 | 0.2653 | - |
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+ | 0.0505 | 150 | 0.2574 | - |
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+ | 0.0674 | 200 | 0.2455 | - |
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+ | 0.0842 | 250 | 0.2583 | - |
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+ | 0.1011 | 300 | 0.2736 | - |
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+ | 0.1179 | 350 | 0.2341 | - |
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+ | 0.1348 | 400 | 0.2524 | - |
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+ | 0.1516 | 450 | 0.2429 | - |
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+ | 0.1685 | 500 | 0.2579 | - |
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+ | 0.1853 | 550 | 0.2363 | - |
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+ | 0.2022 | 600 | 0.2789 | - |
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+ | 0.2190 | 650 | 0.186 | - |
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+ | 0.2358 | 700 | 0.2425 | - |
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+ | 0.2527 | 750 | 0.1963 | - |
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+ | 0.2695 | 800 | 0.1858 | - |
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+ | 0.2864 | 850 | 0.1499 | - |
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+ | 0.3032 | 900 | 0.2219 | - |
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+ | 0.3201 | 950 | 0.1376 | - |
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+ | 0.3369 | 1000 | 0.1115 | - |
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+ | 0.3538 | 1050 | 0.1205 | - |
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+ | 0.3706 | 1100 | 0.1398 | - |
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+ | 0.3875 | 1150 | 0.1585 | - |
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+ | 0.4043 | 1200 | 0.1328 | - |
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+ | 0.4212 | 1250 | 0.0954 | - |
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+ | 0.4380 | 1300 | 0.0707 | - |
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+ | 0.4549 | 1350 | 0.2214 | - |
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+ | 0.4717 | 1400 | 0.1351 | - |
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+ | 0.4885 | 1450 | 0.1249 | - |
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+ | 0.5054 | 1500 | 0.1656 | - |
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+ | 0.5222 | 1550 | 0.1573 | - |
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+ | 0.5391 | 1600 | 0.1103 | - |
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+ | 0.5559 | 1650 | 0.0787 | - |
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+ | 0.5728 | 1700 | 0.126 | - |
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+ | 0.5896 | 1750 | 0.0876 | - |
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+ | 0.6065 | 1800 | 0.1687 | - |
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+ | 0.6233 | 1850 | 0.1319 | - |
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+ | 0.6402 | 1900 | 0.0815 | - |
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+ | 0.6570 | 1950 | 0.09 | - |
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+ | 0.6739 | 2000 | 0.0471 | - |
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+ | 0.6907 | 2050 | 0.1032 | - |
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+ | 0.7075 | 2100 | 0.0858 | - |
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+ | 0.7244 | 2150 | 0.0859 | - |
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+ | 0.7412 | 2200 | 0.0946 | - |
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+ | 0.7581 | 2250 | 0.0618 | - |
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+ | 0.7749 | 2300 | 0.0233 | - |
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+ | 0.7918 | 2350 | 0.0148 | - |
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+ | 0.8086 | 2400 | 0.0367 | - |
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+ | 0.8255 | 2450 | 0.0111 | - |
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+ | 0.8423 | 2500 | 0.0034 | - |
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+ | 0.8592 | 2550 | 0.0174 | - |
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+ | 0.8760 | 2600 | 0.0304 | - |
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+ | 0.8929 | 2650 | 0.0303 | - |
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+ | 0.9097 | 2700 | 0.0031 | - |
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+ | 0.9265 | 2750 | 0.0058 | - |
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+ | 0.9434 | 2800 | 0.0034 | - |
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+ | 0.9602 | 2850 | 0.0011 | - |
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+ | 0.9771 | 2900 | 0.0013 | - |
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+ | 0.9939 | 2950 | 0.0296 | - |
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+ | 1.0108 | 3000 | 0.0008 | - |
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+ | 1.0276 | 3050 | 0.0189 | - |
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+ | 1.0445 | 3100 | 0.0295 | - |
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+ | 1.0613 | 3150 | 0.0276 | - |
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+ | 1.0782 | 3200 | 0.0008 | - |
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+ | 1.0950 | 3250 | 0.0008 | - |
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+ | 1.1119 | 3300 | 0.0009 | - |
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+ | 1.1287 | 3350 | 0.0009 | - |
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+ | 1.1456 | 3400 | 0.0008 | - |
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+ | 1.1624 | 3450 | 0.0099 | - |
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+ | 1.1792 | 3500 | 0.0009 | - |
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+ | 1.1961 | 3550 | 0.0299 | - |
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+ | 1.2129 | 3600 | 0.0007 | - |
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+ | 1.2298 | 3650 | 0.001 | - |
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+ | 1.2466 | 3700 | 0.0009 | - |
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+ | 1.2635 | 3750 | 0.0008 | - |
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+ | 1.2803 | 3800 | 0.001 | - |
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+ | 1.2972 | 3850 | 0.0009 | - |
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+ | 1.3140 | 3900 | 0.0008 | - |
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+ | 1.3309 | 3950 | 0.0007 | - |
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+ | 1.3477 | 4000 | 0.0007 | - |
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+ | 1.3646 | 4050 | 0.03 | - |
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+ | 1.3814 | 4100 | 0.0008 | - |
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+ | 1.3982 | 4150 | 0.0012 | - |
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+ | 1.4151 | 4200 | 0.0292 | - |
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+ | 1.4319 | 4250 | 0.0006 | - |
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+ | 1.4488 | 4300 | 0.0007 | - |
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+ | 1.4656 | 4350 | 0.0006 | - |
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+ | 1.4825 | 4400 | 0.0007 | - |
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+ | 1.4993 | 4450 | 0.0008 | - |
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+ | 1.5162 | 4500 | 0.0008 | - |
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+ | 1.5330 | 4550 | 0.0015 | - |
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+ | 1.5499 | 4600 | 0.0032 | - |
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+ | 1.5667 | 4650 | 0.0015 | - |
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+ | 1.5836 | 4700 | 0.0006 | - |
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+ | 1.6004 | 4750 | 0.0006 | - |
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+ | 1.6173 | 4800 | 0.0021 | - |
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+ | 1.6341 | 4850 | 0.0013 | - |
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+ | 1.6509 | 4900 | 0.0006 | - |
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+ | 1.6678 | 4950 | 0.0006 | - |
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+ | 1.6846 | 5000 | 0.0013 | - |
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+ | 1.7015 | 5050 | 0.0006 | - |
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+ | 1.7183 | 5100 | 0.0007 | - |
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+ | 1.7352 | 5150 | 0.0005 | - |
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+ | 1.7520 | 5200 | 0.0005 | - |
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+ | 1.7689 | 5250 | 0.0006 | - |
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+ | 1.7857 | 5300 | 0.0005 | - |
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+ | 1.8026 | 5350 | 0.0005 | - |
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+ | 1.8194 | 5400 | 0.0005 | - |
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+ | 1.8363 | 5450 | 0.0004 | - |
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+ | 1.8531 | 5500 | 0.0066 | - |
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+ | 1.8699 | 5550 | 0.0005 | - |
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+ | 1.8868 | 5600 | 0.0006 | - |
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+ | 1.9036 | 5650 | 0.0005 | - |
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+ | 1.9205 | 5700 | 0.0005 | - |
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+ | 1.9373 | 5750 | 0.0014 | - |
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+ | 1.9542 | 5800 | 0.0006 | - |
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+ | 1.9710 | 5850 | 0.0004 | - |
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+ | 1.9879 | 5900 | 0.0006 | - |
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+ | 2.0047 | 5950 | 0.0005 | - |
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+ | 2.0216 | 6000 | 0.0006 | - |
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+ | 2.0384 | 6050 | 0.0005 | - |
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+ | 2.0553 | 6100 | 0.0004 | - |
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+ | 2.0721 | 6150 | 0.0012 | - |
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+ | 2.0889 | 6200 | 0.0004 | - |
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+ | 2.1058 | 6250 | 0.0005 | - |
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+ | 2.1226 | 6300 | 0.0004 | - |
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+ | 2.1395 | 6350 | 0.0005 | - |
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+ | 2.1563 | 6400 | 0.0005 | - |
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+ | 2.1732 | 6450 | 0.0005 | - |
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+ | 2.1900 | 6500 | 0.0004 | - |
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+ | 2.2069 | 6550 | 0.0004 | - |
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+ | 2.2237 | 6600 | 0.0005 | - |
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+ | 2.2406 | 6650 | 0.0004 | - |
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+ | 2.2574 | 6700 | 0.0005 | - |
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+ | 2.2743 | 6750 | 0.0004 | - |
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+ | 2.2911 | 6800 | 0.0005 | - |
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+ | 2.3080 | 6850 | 0.0007 | - |
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+ | 2.3248 | 6900 | 0.0004 | - |
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+ | 2.3416 | 6950 | 0.0018 | - |
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+ | 2.3585 | 7000 | 0.0004 | - |
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+ | 2.3753 | 7050 | 0.0004 | - |
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+ | 2.3922 | 7100 | 0.0004 | - |
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+ | 2.4090 | 7150 | 0.0004 | - |
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+ | 2.4259 | 7200 | 0.0004 | - |
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+ | 2.4427 | 7250 | 0.0005 | - |
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+ | 2.4596 | 7300 | 0.0004 | - |
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+ | 2.4764 | 7350 | 0.0005 | - |
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+ | 2.4933 | 7400 | 0.0012 | - |
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+ | 2.5101 | 7450 | 0.0026 | - |
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+ | 2.5270 | 7500 | 0.0004 | - |
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+ | 2.5438 | 7550 | 0.0003 | - |
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+ | 2.5606 | 7600 | 0.0004 | - |
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+ | 2.5775 | 7650 | 0.0004 | - |
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+ | 2.5943 | 7700 | 0.0004 | - |
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+ | 2.6112 | 7750 | 0.0004 | - |
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+ | 2.6280 | 7800 | 0.0004 | - |
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+ | 2.6449 | 7850 | 0.0004 | - |
336
+ | 2.6617 | 7900 | 0.0004 | - |
337
+ | 2.6786 | 7950 | 0.0003 | - |
338
+ | 2.6954 | 8000 | 0.0004 | - |
339
+ | 2.7123 | 8050 | 0.0004 | - |
340
+ | 2.7291 | 8100 | 0.0004 | - |
341
+ | 2.7460 | 8150 | 0.0004 | - |
342
+ | 2.7628 | 8200 | 0.0004 | - |
343
+ | 2.7796 | 8250 | 0.0004 | - |
344
+ | 2.7965 | 8300 | 0.0005 | - |
345
+ | 2.8133 | 8350 | 0.0004 | - |
346
+ | 2.8302 | 8400 | 0.0004 | - |
347
+ | 2.8470 | 8450 | 0.0004 | - |
348
+ | 2.8639 | 8500 | 0.0004 | - |
349
+ | 2.8807 | 8550 | 0.0004 | - |
350
+ | 2.8976 | 8600 | 0.0004 | - |
351
+ | 2.9144 | 8650 | 0.0004 | - |
352
+ | 2.9313 | 8700 | 0.0004 | - |
353
+ | 2.9481 | 8750 | 0.0004 | - |
354
+ | 2.9650 | 8800 | 0.0004 | - |
355
+ | 2.9818 | 8850 | 0.0004 | - |
356
+ | 2.9987 | 8900 | 0.0003 | - |
357
 
358
  ### Framework Versions
359
  - Python: 3.10.12
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