Omar-Nasr commited on
Commit
5662982
1 Parent(s): e6926bf

Add SetFit model

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Files changed (4) hide show
  1. README.md +1000 -30
  2. config.json +1 -1
  3. model.safetensors +1 -1
  4. model_head.pkl +1 -1
README.md CHANGED
@@ -9,18 +9,16 @@ base_model: sentence-transformers/all-roberta-large-v1
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  metrics:
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  - accuracy
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  widget:
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- - text: ' I would do this too but then I run the risk of meeting someone I know lol'
 
 
 
 
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  - text: ' That''s kind of the nature of my volunteer work, but you could volunteer
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  with a food bank or boys and girls club, which would involve more social interaction
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  Just breaking that cycle by going for a short walk around the neighbourhood is
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  a good idea'
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- - text: ' Your body is trying to reduce weight by throwing up and having to go to
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- the bathroon, in case you need to run from the "enemy", so you''ll be lighter'
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- - text: ' But even then, I didn''t have any other problems outside school I still
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- had no friends at European school, I haven''t had any walks which I had constantly
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- with my friends back in Ukraine'
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- - text: ' I like art and nature but you can’t really talk about those for more than
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- a few seconds'
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  pipeline_tag: text-classification
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  inference: true
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  model-index:
@@ -35,7 +33,7 @@ model-index:
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  split: test
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  metrics:
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  - type: accuracy
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- value: 0.3416666666666667
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  name: Accuracy
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  ---
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@@ -67,19 +65,19 @@ 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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- | 1.0 | <ul><li>' and i do biking, i bike for atleast 20mins and towards the end i feel anxious free, less socially anxious too and i do biking, i bike for atleast 20mins and towards the end i feel anxious free, less socially anxious too'</li><li>" That's kind of the nature of my volunteer work, but you could volunteer with a food bank or boys and girls club, which would involve more social interaction Just breaking that cycle by going for a short walk around the neighbourhood is a good idea"</li></ul> |
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- | 2.0 | <ul><li>" I didn't go outside too much"</li><li>' I like art and nature but you can’t really talk about those for more than a few seconds'</li></ul> |
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- | 3.0 | <ul><li>" I don't know anyone in the city, I don't think I have enough courage to go outside alone"</li><li>" But even then, I didn't have any other problems outside school I still had no friends at European school, I haven't had any walks which I had constantly with my friends back in Ukraine"</li></ul> |
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- | 0.0 | <ul><li>' Your body is trying to reduce weight by throwing up and having to go to the bathroon, in case you need to run from the "enemy", so you\'ll be lighter'</li><li>' I would do this too but then I run the risk of meeting someone I know lol'</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** | 0.3417 |
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  ## Uses
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@@ -99,7 +97,7 @@ from setfit import SetFitModel
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  # Download from the 🤗 Hub
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  model = SetFitModel.from_pretrained("Omar-Nasr/setfitmodel")
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  # Run inference
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- preds = model(" I would do this too but then I run the risk of meeting someone I know lol")
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  ```
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  <!--
@@ -129,19 +127,19 @@ preds = model(" I would do this too but then I run the risk of meeting someone I
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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 | 7 | 27.375 | 47 |
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  | Label | Training Sample Count |
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  |:------|:----------------------|
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- | 0.0 | 2 |
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- | 1.0 | 2 |
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- | 2.0 | 2 |
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- | 3.0 | 2 |
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  ### Training Hyperparameters
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- - batch_size: (16, 16)
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  - num_epochs: (4, 4)
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  - max_steps: -1
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  - sampling_strategy: oversampling
@@ -158,17 +156,989 @@ preds = model(" I would do this too but then I run the risk of meeting someone I
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  - load_best_model_at_end: False
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  ### Training Results
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- | Epoch | Step | Training Loss | Validation Loss |
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- |:------:|:----:|:-------------:|:---------------:|
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- | 0.3333 | 1 | 0.0708 | - |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework Versions
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  - Python: 3.10.13
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  - SetFit: 1.0.3
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  - Sentence Transformers: 2.7.0
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- - Transformers: 4.38.1
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  - PyTorch: 2.1.2
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- - Datasets: 2.19.0
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  - Tokenizers: 0.15.2
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  ## Citation
 
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  metrics:
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  - accuracy
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  widget:
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+ - text: ' I''m a runner and I have to say you''re wrong'
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+ - text: ' I walk everywhere on foot and I feel like the greatest loser in my city
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+ I have tendonitis in both knees from long distance running (my last favorite hobby
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+ which I can''t even do anymore) I''ve wasted my prime years'
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+ - text: I can't water the garden because my neighbours are watching
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  - text: ' That''s kind of the nature of my volunteer work, but you could volunteer
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  with a food bank or boys and girls club, which would involve more social interaction
19
  Just breaking that cycle by going for a short walk around the neighbourhood is
20
  a good idea'
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+ - text: ' Like jumping into a pool, or starting an assignment'
 
 
 
 
 
 
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  pipeline_tag: text-classification
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  inference: true
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  model-index:
 
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  split: test
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  metrics:
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  - type: accuracy
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+ value: 0.4766666666666667
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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)
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  ### Model Labels
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+ | Label | Examples |
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+ |:------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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+ | 3.0 | <ul><li>"It's whenever I look someone in the eye, when I'm on my bike or when I'm walking somewhere, I feel like they look at me and ridicule me in their headsIt's whenever I look someone in the eye, when I'm on my bike or when I'm walking somewhere, I feel like they look at me and ridicule me in their heads"</li><li>" While I ended up making progress, it wasn't as fast as I had hoped and I still had a lot of trouble doing some things (such as jogging in public)"</li><li>' My social anxiety has got a lot worse as there’s been a lot of recent trauma and I can’t even go outside anymore, a social worker cane to visit and agreed that she’d help me get counselling at home, I’m hoping soon I’ll start getting better'</li></ul> |
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+ | 0.0 | <ul><li>' holy shit the food runs with people visiting lol'</li><li>" The problem with doing this is you're just laying there and not focusing on any outside activities and thus you become prey to hell lot of negative thoughts"</li><li>' You might feel relaxed not having to deal with people, but trust me humans are social creatures and in the long run you’re going to become miserable from loneliness'</li></ul> |
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+ | 1.0 | <ul><li>' I run 8'</li><li>" Is there anything actually wrong with your legs, or are you just imagining things? Are they really staring at you, or is it in your head? If you can't deal with going out on your own, try going outside with someone you're comfortable with"</li><li>' Being outside is an extra plus!! Keep going :) '</li></ul> |
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+ | 2.0 | <ul><li>' It summer time and I have plans to hike and do other fun stuff but i cant do them myself '</li><li>' She knows that I barely go outside and tries to get me to go to out but only with muslims cause she believes that other kids are bad for me'</li><li>' It depends on if you live in an area where getting around on a bike is a viable option I’ve heard of people delivering Doordash or Postmates on bicycles but it generally is only more viable if you live in an urban area where restaurants and delivery addresses are closer together, in a suburban area that is more car-focused it’s difficult Though if deliveries are slow they will usually make you do other tasks around the restaurant, whereas with apps you can either run multiple apps at once or just fuck around between deliveries if it’s slow '</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** | 0.4767 |
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  ## Uses
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  # Download from the 🤗 Hub
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  model = SetFitModel.from_pretrained("Omar-Nasr/setfitmodel")
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  # Run inference
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+ preds = model(" I'm a runner and I have to say you're wrong")
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  ```
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  <!--
 
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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 | 3 | 40.3722 | 1083 |
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  | Label | Training Sample Count |
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  |:------|:----------------------|
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+ | 0.0 | 90 |
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+ | 1.0 | 90 |
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+ | 2.0 | 90 |
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+ | 3.0 | 90 |
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  ### Training Hyperparameters
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+ - batch_size: (8, 8)
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  - num_epochs: (4, 4)
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  - max_steps: -1
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  - sampling_strategy: oversampling
 
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  - load_best_model_at_end: False
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  ### Training Results
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+ | Epoch | Step | Training Loss | Validation Loss |
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+ |:------:|:-----:|:-------------:|:---------------:|
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+ | 0.0001 | 1 | 0.2936 | - |
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+ | 0.0041 | 50 | 0.3404 | - |
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+ | 0.0082 | 100 | 0.2465 | - |
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+ | 0.0123 | 150 | 0.287 | - |
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+ | 0.0165 | 200 | 0.1955 | - |
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+ | 0.0206 | 250 | 0.2187 | - |
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+ | 0.0247 | 300 | 0.2239 | - |
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+ | 0.0288 | 350 | 0.2709 | - |
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+ | 0.0329 | 400 | 0.2919 | - |
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+ | 0.0370 | 450 | 0.2689 | - |
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+ | 0.0412 | 500 | 0.176 | - |
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+ | 0.0453 | 550 | 0.2699 | - |
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+ | 0.0494 | 600 | 0.2538 | - |
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+ | 0.0535 | 650 | 0.2029 | - |
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+ | 0.0576 | 700 | 0.2566 | - |
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+ | 0.0617 | 750 | 0.1106 | - |
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+ | 0.0658 | 800 | 0.1625 | - |
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+ | 0.0700 | 850 | 0.1276 | - |
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+ | 0.0741 | 900 | 0.1603 | - |
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+ | 0.0782 | 950 | 0.0294 | - |
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+ | 0.0823 | 1000 | 0.011 | - |
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+ | 0.0864 | 1050 | 0.1924 | - |
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+ | 0.0905 | 1100 | 0.0149 | - |
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+ | 0.0947 | 1150 | 0.1249 | - |
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+ | 0.0988 | 1200 | 0.1251 | - |
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+ | 0.1029 | 1250 | 0.008 | - |
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+ | 0.1070 | 1300 | 0.0008 | - |
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+ | 0.1111 | 1350 | 0.009 | - |
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+ | 0.1152 | 1400 | 0.0007 | - |
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+ | 0.1193 | 1450 | 0.0013 | - |
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+ | 0.1235 | 1500 | 0.0016 | - |
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+ | 0.1276 | 1550 | 0.0042 | - |
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+ | 0.1317 | 1600 | 0.0003 | - |
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+ | 0.1358 | 1650 | 0.0002 | - |
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+ | 0.1399 | 1700 | 0.0003 | - |
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+ | 0.1440 | 1750 | 0.0002 | - |
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+ | 0.1481 | 1800 | 0.0002 | - |
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+ | 0.1523 | 1850 | 0.0002 | - |
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+ | 0.1564 | 1900 | 0.0003 | - |
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+ | 0.1605 | 1950 | 0.0001 | - |
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+ | 0.1646 | 2000 | 0.0001 | - |
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+ | 0.1687 | 2050 | 0.0002 | - |
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+ | 0.1728 | 2100 | 0.0001 | - |
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+ | 0.1770 | 2150 | 0.0001 | - |
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+ | 0.1811 | 2200 | 0.0001 | - |
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+ | 0.1852 | 2250 | 0.0001 | - |
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+ | 0.1893 | 2300 | 0.0001 | - |
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+ | 0.1934 | 2350 | 0.0002 | - |
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+ | 0.1975 | 2400 | 0.0001 | - |
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+ | 0.2016 | 2450 | 0.0002 | - |
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+ | 0.2058 | 2500 | 0.0001 | - |
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+ | 0.2099 | 2550 | 0.0001 | - |
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+ | 0.2140 | 2600 | 0.0001 | - |
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+ | 0.2181 | 2650 | 0.0 | - |
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+ | 0.2222 | 2700 | 0.0001 | - |
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+ | 0.2263 | 2750 | 0.0001 | - |
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+ | 0.2305 | 2800 | 0.0001 | - |
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+ | 0.2346 | 2850 | 0.0 | - |
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+ | 0.2387 | 2900 | 0.0 | - |
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+ | 0.2428 | 2950 | 0.0001 | - |
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+ | 0.2469 | 3000 | 0.0001 | - |
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+ | 0.2510 | 3050 | 0.0002 | - |
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+ | 0.2551 | 3100 | 0.0001 | - |
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+ | 0.2593 | 3150 | 0.0 | - |
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+ | 0.2634 | 3200 | 0.0 | - |
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+ | 0.2675 | 3250 | 0.0001 | - |
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+ | 0.2716 | 3300 | 0.0001 | - |
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+ | 0.2757 | 3350 | 0.0 | - |
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+ | 0.2798 | 3400 | 0.0 | - |
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+ | 0.2840 | 3450 | 0.0 | - |
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+ | 0.2881 | 3500 | 0.0 | - |
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+ | 0.2922 | 3550 | 0.0 | - |
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+ | 0.2963 | 3600 | 0.0 | - |
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+ | 0.3004 | 3650 | 0.0 | - |
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+ | 0.3045 | 3700 | 0.0 | - |
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+ | 0.3086 | 3750 | 0.0001 | - |
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+ | 0.3128 | 3800 | 0.0 | - |
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+ | 0.3169 | 3850 | 0.0 | - |
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+ | 0.3210 | 3900 | 0.0001 | - |
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+ | 0.3251 | 3950 | 0.0001 | - |
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+ | 0.3292 | 4000 | 0.0 | - |
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+ | 0.3333 | 4050 | 0.0001 | - |
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+ | 0.3374 | 4100 | 0.0 | - |
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+ | 0.3416 | 4150 | 0.0 | - |
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+ | 0.3457 | 4200 | 0.482 | - |
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+ | 0.3498 | 4250 | 0.0384 | - |
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+ | 0.3539 | 4300 | 0.1998 | - |
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+ | 0.3580 | 4350 | 0.2232 | - |
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+ | 0.3621 | 4400 | 0.1794 | - |
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+ | 0.3663 | 4450 | 0.0911 | - |
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+ | 0.3704 | 4500 | 0.1016 | - |
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+ | 0.3745 | 4550 | 0.1266 | - |
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+ | 0.3786 | 4600 | 0.0004 | - |
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+ | 0.3827 | 4650 | 0.0005 | - |
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+ | 0.3868 | 4700 | 0.0001 | - |
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+ | 0.3909 | 4750 | 0.0002 | - |
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+ | 0.3951 | 4800 | 0.0005 | - |
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+ | 0.3992 | 4850 | 0.0001 | - |
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+ | 0.4033 | 4900 | 0.0003 | - |
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+ | 0.4074 | 4950 | 0.0002 | - |
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+ | 0.4115 | 5000 | 0.0001 | - |
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+ | 0.4156 | 5050 | 0.0001 | - |
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+ | 0.4198 | 5100 | 0.0001 | - |
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+ | 0.4239 | 5150 | 0.0 | - |
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+ | 0.4280 | 5200 | 0.0 | - |
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+ | 0.4321 | 5250 | 0.0 | - |
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+ | 0.4362 | 5300 | 0.0001 | - |
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+ | 0.4403 | 5350 | 0.0 | - |
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+ | 0.4444 | 5400 | 0.0 | - |
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+ | 0.4486 | 5450 | 0.0 | - |
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+ | 0.4527 | 5500 | 0.0 | - |
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+ | 0.4568 | 5550 | 0.0001 | - |
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+ | 0.4609 | 5600 | 0.0 | - |
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+ | 0.4650 | 5650 | 0.0 | - |
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+ | 0.4691 | 5700 | 0.0 | - |
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+ | 0.4733 | 5750 | 0.0001 | - |
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+ | 0.4774 | 5800 | 0.0 | - |
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+ | 0.4815 | 5850 | 0.0 | - |
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+ | 0.4856 | 5900 | 0.0 | - |
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+ | 0.4897 | 5950 | 0.0 | - |
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+ | 0.4938 | 6000 | 0.0 | - |
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+ | 0.4979 | 6050 | 0.0001 | - |
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+ | 0.5021 | 6100 | 0.0 | - |
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+ | 0.5062 | 6150 | 0.0 | - |
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+ | 0.5103 | 6200 | 0.0 | - |
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+ | 0.5144 | 6250 | 0.0 | - |
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+ | 0.5185 | 6300 | 0.0 | - |
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+ | 0.5226 | 6350 | 0.0 | - |
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+ | 0.5267 | 6400 | 0.0 | - |
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+ | 0.5309 | 6450 | 0.0 | - |
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+ | 0.5350 | 6500 | 0.0 | - |
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+ | 0.5391 | 6550 | 0.0 | - |
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+ | 0.5432 | 6600 | 0.0 | - |
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+ | 0.5473 | 6650 | 0.0 | - |
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+ | 0.5514 | 6700 | 0.0 | - |
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+ | 0.5556 | 6750 | 0.0 | - |
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+ | 0.5597 | 6800 | 0.0 | - |
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+ | 0.5638 | 6850 | 0.0 | - |
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+ | 0.5679 | 6900 | 0.0 | - |
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+ | 0.5720 | 6950 | 0.0 | - |
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+ | 0.5761 | 7000 | 0.0 | - |
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+ | 0.5802 | 7050 | 0.0 | - |
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+ | 0.5844 | 7100 | 0.0 | - |
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+ | 0.5885 | 7150 | 0.0 | - |
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+ | 0.5926 | 7200 | 0.0 | - |
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+ | 0.5967 | 7250 | 0.0001 | - |
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+ | 0.6008 | 7300 | 0.0 | - |
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+ | 0.6049 | 7350 | 0.0 | - |
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+ | 0.6091 | 7400 | 0.0 | - |
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+ | 0.6132 | 7450 | 0.0 | - |
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+ | 0.6173 | 7500 | 0.0 | - |
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+ | 0.6214 | 7550 | 0.0 | - |
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+ | 0.6255 | 7600 | 0.0 | - |
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+ | 0.6296 | 7650 | 0.0 | - |
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+ | 0.6337 | 7700 | 0.0 | - |
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+ | 0.6379 | 7750 | 0.0 | - |
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+ | 0.6420 | 7800 | 0.0 | - |
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+ | 0.6461 | 7850 | 0.0 | - |
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+ | 0.6502 | 7900 | 0.001 | - |
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+ | 0.6543 | 7950 | 0.0061 | - |
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+ | 0.6584 | 8000 | 0.0966 | - |
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+ | 0.6626 | 8050 | 0.0911 | - |
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+ | 0.6667 | 8100 | 0.1791 | - |
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+ | 0.6708 | 8150 | 0.0001 | - |
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+ | 0.6749 | 8200 | 0.0354 | - |
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+ | 0.6790 | 8250 | 0.0061 | - |
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+ | 0.6831 | 8300 | 0.0 | - |
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+ | 0.6872 | 8350 | 0.0 | - |
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+ | 0.6914 | 8400 | 0.0001 | - |
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+ | 0.6955 | 8450 | 0.0 | - |
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+ | 0.6996 | 8500 | 0.0 | - |
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+ | 0.7037 | 8550 | 0.0 | - |
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+ | 0.7078 | 8600 | 0.0 | - |
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+ | 0.7119 | 8650 | 0.0 | - |
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+ | 0.7160 | 8700 | 0.0 | - |
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+ | 0.7202 | 8750 | 0.0 | - |
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+ | 0.7243 | 8800 | 0.0 | - |
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+ | 0.7284 | 8850 | 0.0 | - |
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+ | 0.7325 | 8900 | 0.0 | - |
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+ | 0.7366 | 8950 | 0.0 | - |
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+ | 0.7407 | 9000 | 0.0 | - |
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+ | 0.7449 | 9050 | 0.0 | - |
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+ | 0.7490 | 9100 | 0.0001 | - |
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+ | 0.7531 | 9150 | 0.0 | - |
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+ | 0.7572 | 9200 | 0.0 | - |
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+ | 0.7613 | 9250 | 0.0 | - |
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+ | 0.7654 | 9300 | 0.0 | - |
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+ | 0.7695 | 9350 | 0.0 | - |
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+ | 0.7737 | 9400 | 0.0 | - |
350
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351
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352
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353
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354
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355
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356
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357
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358
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360
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361
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362
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363
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364
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366
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367
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368
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369
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370
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371
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372
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373
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374
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375
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376
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377
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378
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379
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380
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381
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382
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383
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384
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385
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386
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387
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388
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389
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390
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391
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392
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393
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395
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396
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399
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400
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401
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402
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403
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407
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411
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413
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414
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415
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417
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418
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419
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420
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426
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428
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429
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431
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449
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456
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465
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470
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484
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485
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486
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487
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488
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489
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490
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491
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492
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493
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494
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497
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498
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499
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500
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501
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502
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503
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504
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509
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511
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515
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517
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518
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520
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521
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526
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527
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528
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529
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530
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531
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532
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533
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534
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535
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536
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537
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538
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539
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540
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541
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542
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543
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544
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545
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546
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547
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548
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549
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550
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551
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552
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553
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554
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555
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556
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557
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558
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559
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560
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561
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562
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563
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564
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565
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566
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567
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568
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569
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570
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571
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572
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573
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574
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575
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576
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577
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578
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579
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580
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581
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582
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583
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584
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585
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587
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588
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589
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590
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591
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592
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594
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595
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596
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597
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598
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599
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601
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602
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603
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604
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605
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606
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607
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608
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609
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610
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611
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612
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613
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614
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615
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616
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617
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618
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619
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620
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621
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622
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623
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624
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625
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626
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627
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628
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629
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630
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631
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632
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633
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634
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635
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636
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637
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638
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639
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640
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641
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642
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643
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644
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645
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646
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647
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648
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649
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650
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651
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652
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653
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654
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655
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656
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657
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658
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659
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660
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661
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662
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663
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664
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665
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666
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667
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668
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669
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670
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671
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672
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673
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674
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675
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676
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677
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678
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679
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680
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681
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682
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683
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684
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685
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686
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687
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688
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689
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690
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691
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692
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693
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694
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695
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696
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697
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698
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699
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700
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701
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702
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703
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704
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705
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706
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707
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708
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709
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710
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711
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712
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713
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714
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715
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716
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717
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718
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719
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720
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721
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722
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723
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724
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725
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726
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727
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728
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729
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730
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731
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732
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733
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734
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735
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736
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737
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738
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739
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740
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741
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742
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912
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915
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924
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925
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930
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933
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935
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936
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937
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938
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939
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940
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945
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952
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954
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955
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956
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967
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969
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981
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987
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988
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990
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991
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993
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994
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996
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997
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998
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1000
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1001
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1002
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1003
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1004
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1006
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1009
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1010
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1011
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1012
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1013
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1014
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1015
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1017
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1018
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1019
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1020
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1023
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1024
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1025
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1026
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1027
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1028
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1029
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1030
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1031
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1032
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1033
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1034
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1035
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1036
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1037
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1038
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1039
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1040
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1041
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1042
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1043
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1044
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1045
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1046
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1047
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1048
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1049
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1050
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1051
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1052
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1053
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1054
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1055
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1056
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1057
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1058
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1059
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1060
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1061
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1062
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1063
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1064
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1065
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1066
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1067
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1068
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1069
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1070
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1071
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1072
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1073
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1074
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1075
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1076
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1077
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1078
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1079
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1080
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1081
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1082
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1083
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1084
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1085
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1086
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1087
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1088
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1089
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1090
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1091
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1092
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1093
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1094
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1095
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1096
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1097
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1098
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1099
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1100
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1101
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1102
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1103
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1104
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1105
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1106
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1107
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1108
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1109
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1110
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1111
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1112
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1113
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1114
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1115
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1116
+ | 3.9300 | 47750 | 0.0 | - |
1117
+ | 3.9342 | 47800 | 0.0 | - |
1118
+ | 3.9383 | 47850 | 0.0 | - |
1119
+ | 3.9424 | 47900 | 0.0 | - |
1120
+ | 3.9465 | 47950 | 0.0 | - |
1121
+ | 3.9506 | 48000 | 0.0 | - |
1122
+ | 3.9547 | 48050 | 0.0 | - |
1123
+ | 3.9588 | 48100 | 0.0 | - |
1124
+ | 3.9630 | 48150 | 0.0 | - |
1125
+ | 3.9671 | 48200 | 0.0 | - |
1126
+ | 3.9712 | 48250 | 0.0 | - |
1127
+ | 3.9753 | 48300 | 0.0 | - |
1128
+ | 3.9794 | 48350 | 0.0 | - |
1129
+ | 3.9835 | 48400 | 0.0 | - |
1130
+ | 3.9877 | 48450 | 0.0 | - |
1131
+ | 3.9918 | 48500 | 0.0 | - |
1132
+ | 3.9959 | 48550 | 0.0 | - |
1133
+ | 4.0 | 48600 | 0.0 | - |
1134
 
1135
  ### Framework Versions
1136
  - Python: 3.10.13
1137
  - SetFit: 1.0.3
1138
  - Sentence Transformers: 2.7.0
1139
+ - Transformers: 4.39.3
1140
  - PyTorch: 2.1.2
1141
+ - Datasets: 2.18.0
1142
  - Tokenizers: 0.15.2
1143
 
1144
  ## Citation
config.json CHANGED
@@ -21,7 +21,7 @@
21
  "pad_token_id": 1,
22
  "position_embedding_type": "absolute",
23
  "torch_dtype": "float32",
24
- "transformers_version": "4.38.1",
25
  "type_vocab_size": 1,
26
  "use_cache": true,
27
  "vocab_size": 50265
 
21
  "pad_token_id": 1,
22
  "position_embedding_type": "absolute",
23
  "torch_dtype": "float32",
24
+ "transformers_version": "4.39.3",
25
  "type_vocab_size": 1,
26
  "use_cache": true,
27
  "vocab_size": 50265
model.safetensors CHANGED
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  size 1421483904
 
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  size 1421483904
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  size 33639
 
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  size 33639