Push model using huggingface_hub.
Browse files- README.md +75 -76
- model.safetensors +1 -1
- model_head.pkl +1 -1
README.md
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- text-classification
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- generated_from_setfit_trainer
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widget:
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- text: هاد سعودي ، وانت خليك بحالك يا سوري ولا انت تقليد سوري
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inference: true
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model-index:
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- name: SetFit with akhooli/sbert_ar_nli_500k_ubc_norm
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split: test
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metrics:
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- type: accuracy
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value: 0.
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name: Accuracy
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---
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@@ -63,17 +62,17 @@ The model has been trained using an efficient few-shot learning technique that i
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- **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
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### Model Labels
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| Label | Examples
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| negative | <ul><li>'
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| positive | <ul><li>'
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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.
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## Uses
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# Download from the 🤗 Hub
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model = SetFitModel.from_pretrained("akhooli/setfit_ar_ubc_hs")
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# Run inference
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preds = model("
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```
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<!--
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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 |
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| Label | Training Sample Count |
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|:---------|:----------------------|
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| negative |
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| positive |
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### Training Hyperparameters
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- batch_size: (32, 32)
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- warmup_proportion: 0.1
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- l2_weight: 0.01
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- seed: 42
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- run_name:
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- eval_max_steps: -1
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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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| 0.0003 | 1 | 0.
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| 0.0333 | 100 | 0.
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| 0.0667 | 200 | 0.
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| 0.1 | 300 | 0.
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| 0.1333 | 400 | 0.
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| 0.1667 | 500 | 0.
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| 0.2 | 600 | 0.
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| 0.2333 | 700 | 0.
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| 0.2667 | 800 | 0.
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| 0.3 | 900 | 0.
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| 0.3333 | 1000 | 0.
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| 0.3667 | 1100 | 0.
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| 0.4 | 1200 | 0.
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| 0.4333 | 1300 | 0.
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| 0.4667 | 1400 | 0.
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| 0.5 | 1500 | 0.
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| 0.5333 | 1600 | 0.
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| 0.5667 | 1700 | 0.
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| 0.6 | 1800 | 0.
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| 0.6333 | 1900 | 0.
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| 0.6667 | 2000 | 0.
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| 0.7 | 2100 | 0.
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| 0.7333 | 2200 | 0.
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| 0.7667 | 2300 | 0.
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| 0.8 | 2400 | 0.
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| 0.8333 | 2500 | 0.
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| 0.8667 | 2600 | 0.
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| 0.9 | 2700 | 0.
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| 0.9333 | 2800 | 0.
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| 0.9667 | 2900 | 0.
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| 1.0 | 3000 | 0.002 | - |
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| 1.0333 | 3100 | 0.
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| 1.0667 | 3200 | 0.0022 | - |
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| 1.1 | 3300 | 0.
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| 1.1333 | 3400 | 0.
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| 1.1667 | 3500 | 0.
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| 1.2 | 3600 | 0.
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| 1.2333 | 3700 | 0.
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| 1.2667 | 3800 | 0.
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| 1.3 | 3900 | 0.
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| 1.3333 | 4000 | 0.0013 | - |
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| 1.3667 | 4100 | 0.
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| 1.4 | 4200 | 0.
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| 1.4333 | 4300 | 0.
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| 1.5 | 4500 | 0.
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| 1.6 | 4800 | 0.
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| 1.6333 | 4900 | 0.
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| 1.6667 | 5000 | 0.
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| 1.7 | 5100 | 0.
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| 1.7333 | 5200 | 0.
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| 1.7667 | 5300 | 0.
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| 1.8 | 5400 | 0.
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| 1.8333 | 5500 | 0.
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| 1.8667 | 5600 | 0.
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| 1.9 | 5700 | 0.
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| 1.9333 | 5800 | 0.
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| 1.9667 | 5900 | 0.0001 | - |
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| 2.0 | 6000 | 0.
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### Framework Versions
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- Python: 3.10.14
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- text-classification
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- generated_from_setfit_trainer
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widget:
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- text: كيف كل زمن وإله أتباعه الزقيفة بإيام الإحتلال السوري للبنان، كان أشهرهم ناصر
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قنديل زال الوجود العسكري وتبخ...
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- text: اداي في كتير مشحرين وقلال عقل في لبنان بقصد الذين يمدحون ويمجدون شخص مخلوق
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من لحم ونسوا ان الله هو من ي...
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- text: كول هوا و سد نيعك
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- text: لا تحبسنا على غدر الزمان طالما نحن لها في المرصاد
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- text: العمر الو حق مبين عليكي الكبر
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inference: true
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model-index:
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- name: SetFit with akhooli/sbert_ar_nli_500k_ubc_norm
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split: test
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metrics:
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- type: accuracy
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value: 0.8625363020329139
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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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| negative | <ul><li>'جبران باسيل يغرّد عن رحيل مي منسى لبنان سيفتقد روحك الجميلة'</li><li>'نشرتكم مقابلة لوزير الخارجية اللبناني جبران باسيل مع سي أن أن تثير الجدل على منصات التواصل ما السبب؟'</li><li>' حسا السنه حسا الشيعه حسا الحضران والبدوان\nتساوينا بمحبتها وساوتنا أراضيها\n🌴\nعساني يالحسا فدوة فديت الداار والسكان\nمن اول بيت لآخر بيت بقراها وحواريها\n🌴\nمكانك يالحسا عالي وقدرك فوق مهما كان\nومن حاول يقارن بك بيخسر في تواليها\n🌴وس��امتكم🌴'</li></ul> |
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| positive | <ul><li>'جبران باسيل اكثر الساسة نفاقا'</li><li>'انا اقترح عليك طبيب بيطري'</li><li>'انتي شكلك مو سورية بس عم تزعمي'</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** | 0.8625 |
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## Uses
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# Download from the 🤗 Hub
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model = SetFitModel.from_pretrained("akhooli/setfit_ar_ubc_hs")
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# Run inference
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preds = model("كول هوا و سد نيعك")
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```
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<!--
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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 | 16.5047 | 102 |
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| Label | Training Sample Count |
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|:---------|:----------------------|
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| negative | 3709 |
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| positive | 3800 |
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### Training Hyperparameters
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- batch_size: (32, 32)
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- warmup_proportion: 0.1
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- l2_weight: 0.01
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- seed: 42
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- run_name: setfit_hate_38k_ubc_6k
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- eval_max_steps: -1
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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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| 0.0003 | 1 | 0.3147 | - |
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| 0.0333 | 100 | 0.2724 | - |
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| 0.0667 | 200 | 0.2165 | - |
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| 0.1 | 300 | 0.163 | - |
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| 0.1333 | 400 | 0.1275 | - |
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| 0.1667 | 500 | 0.0939 | - |
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| 0.2 | 600 | 0.0725 | - |
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| 0.2333 | 700 | 0.0535 | - |
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| 0.2667 | 800 | 0.041 | - |
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| 0.3 | 900 | 0.0369 | - |
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| 0.3333 | 1000 | 0.0286 | - |
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| 0.3667 | 1100 | 0.0202 | - |
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| 0.4 | 1200 | 0.0186 | - |
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| 0.7333 | 2200 | 0.0026 | - |
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| 0.7667 | 2300 | 0.0042 | - |
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| 0.8 | 2400 | 0.0022 | - |
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| 0.8667 | 2600 | 0.0031 | - |
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| 0.9 | 2700 | 0.0031 | - |
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| 0.9667 | 2900 | 0.0032 | - |
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| 1.0333 | 3100 | 0.0012 | - |
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| 1.1 | 3300 | 0.0012 | - |
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| 2.0 | 6000 | 0.0007 | - |
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### Framework Versions
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- Python: 3.10.14
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 651387752
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model_head.pkl
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oid sha256:
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size 7007
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size 7007
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