| Description: |
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| - trained on text classification of type of net zero target. Text is from company ESG reports, data is labelled by Net Zero Tracker. |
| - text was truncated to 128 tokens before tokenization. |
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| Problems: |
| - keeps outputting the same label regardless of input |
| - The text column is quite unstructured, varies in lenghth, some include/don't include URL, some include excerpts from ESG report, etc... |
| - truncation might have resulted in loss of data |
| - should try text generation task instead |
| - too many labels makes model behave poorly. |
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| Moving Forward: |
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| - better text preprocessing, remove urls, etc... |
| - change task to text generation. Might perform better (This means ClimateBert cannot be used as base model.) |
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