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--- |
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license: apache-2.0 |
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language: "en" |
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tags: |
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- financial-sentiment-analysis |
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- sentiment-analysis |
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- generated_from_trainer |
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- financial |
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- stocks |
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- sentiment |
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metrics: |
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- f1 |
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datasets: |
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- financial_phrasebank |
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- Kaggle Self label |
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- financial-classification |
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widget: |
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- text: "The USD rallied by 10% last night" |
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example_title: "Bullish Sentiment" |
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- text: "Covid-19 cases have been increasing over the past few months" |
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example_title: "Bearish Sentiment" |
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- text: "the USD has been trending lower" |
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example_title: "Mildly Bearish Sentiment" |
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model-index: |
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- name: distilroberta-finetuned-finclass |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# distilroberta-finetuned-finclass |
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This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the [financial-phrasebank + Kaggle Dataset](https://huggingface.co/datasets/nickmuchi/financial-classification) dataset. The Kaggle dataset includes Covid-19 sentiment data and can be found here: [sentiment-classification-selflabel-dataset](https://www.kaggle.com/percyzheng/sentiment-classification-selflabel-dataset). |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4463 |
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- F1: 0.8835 |
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## Model description |
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Model determines the financial sentiment of given text. |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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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: 2e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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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: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.7309 | 1.0 | 72 | 0.3671 | 0.8441 | |
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| 0.3757 | 2.0 | 144 | 0.3199 | 0.8709 | |
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| 0.3054 | 3.0 | 216 | 0.3096 | 0.8678 | |
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| 0.2229 | 4.0 | 288 | 0.3776 | 0.8390 | |
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| 0.1744 | 5.0 | 360 | 0.3678 | 0.8723 | |
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| 0.1436 | 6.0 | 432 | 0.3728 | 0.8758 | |
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| 0.1044 | 7.0 | 504 | 0.4116 | 0.8744 | |
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| 0.0931 | 8.0 | 576 | 0.4148 | 0.8761 | |
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| 0.0683 | 9.0 | 648 | 0.4423 | 0.8837 | |
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| 0.0611 | 10.0 | 720 | 0.4463 | 0.8835 | |
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### Framework versions |
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- Transformers 4.15.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.0 |
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- Tokenizers 0.10.3 |
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