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@@ -83,11 +83,11 @@ https://github.com/nicolay-r/Reasoning-for-Sentiment-Analysis-Framework
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  Google-colab notebook for reproduction:
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  https://colab.research.google.com/github/nicolay-r/Reasoning-for-Sentiment-Analysis-Framework/blob/main/Reasoning_for_Sentiment_Analysis_Framework.ipynb
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- **Setup:** `Flan-T5-base`, output up to 300 tokens, 5 epochs, 16-batch size.
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  **GPU:** `NVidia-A100`, ~4 min/epoch, temperature 1.0, float 32
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- The overall training process took **4 epochs**.
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  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64e62d11d27a8292c3637f86/JwCP0EIe6q1VVdNrTzPQl.png)
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@@ -118,11 +118,11 @@ The test evaluation for this model [showcases](https://arxiv.org/abs/2404.12342)
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  Below is the log of the training process that showcases the final peformance on the RuSentNE-2023 `test` set after 4 epochs (lines 5-6):
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  ```tsv
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  F1_PN F1_PN0 default mode
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- 0 60.270 69.261 69.261 valid
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- 1 66.226 73.596 73.596 valid
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- 2 65.704 73.675 73.675 valid
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- 3 66.729 74.186 74.186 valid
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- 4 67.314 74.669 74.669 valid
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- 5 62.715 71.001 71.001 test
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- 6 62.715 71.001 71.001 test
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  ```
 
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  Google-colab notebook for reproduction:
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  https://colab.research.google.com/github/nicolay-r/Reasoning-for-Sentiment-Analysis-Framework/blob/main/Reasoning_for_Sentiment_Analysis_Framework.ipynb
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+ **Setup:** `Flan-T5-base`, output up to 300 tokens, 16-batch size.
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  **GPU:** `NVidia-A100`, ~4 min/epoch, temperature 1.0, float 32
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+ The overall training process took **5 epochs**.
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  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64e62d11d27a8292c3637f86/JwCP0EIe6q1VVdNrTzPQl.png)
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  Below is the log of the training process that showcases the final peformance on the RuSentNE-2023 `test` set after 4 epochs (lines 5-6):
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  ```tsv
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  F1_PN F1_PN0 default mode
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+ 0 45.523 59.375 59.375 valid
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+ 1 62.345 70.260 70.260 valid
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+ 2 62.722 70.704 70.704 valid
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+ 3 62.721 70.671 70.671 valid
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+ 4 62.357 70.247 70.247 valid
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+ 5 60.024 68.171 68.171 test
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+ 6 60.024 68.171 68.171 test
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  ```