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--- |
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tags: |
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- generated_from_trainer |
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- summarization |
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- finance |
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model-index: |
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- name: BART-10K-Summarization |
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results: [] |
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--- |
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# BART-10K-Summarization |
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This model is a fine-tuned version of Facebook's BART model specifically for summarizing financial 10K report sections. |
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## Model description |
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BART-10K-Summarization is designed to produce concise summaries of detailed financial reports, assisting analysts and stakeholders in quickly understanding key information without needing to parse the entire document. |
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## Intended uses & limitations |
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This model is intended to aid financial analysts, investors, and regulatory bodies by summarizing sections of 10K reports. It may not perform well on non-financial texts or highly technical documents outside the scope of standard financial reporting. |
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## Training and evaluation data |
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The model was trained on a curated dataset of 10K financial reports, each annotated with executive summaries by experienced financial analysts. |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3.0 |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.1+cu121 |
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- Tokenizers 0.19.1 |
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