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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- financial_phrasebank |
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metrics: |
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- f1 |
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model-index: |
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- name: FIN_BERT_sentiment |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: financial_phrasebank |
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type: financial_phrasebank |
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config: sentences_66agree |
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split: train |
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args: sentences_66agree |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.8890693407692588 |
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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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# FIN_BERT_sentiment |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the financial_phrasebank dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4905 |
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- F1: 0.8891 |
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- Acc: 0.8886 |
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## Model description |
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More information needed |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Acc | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| 0.5295 | 1.0 | 211 | 0.3757 | 0.8731 | 0.8720 | |
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| 0.2174 | 2.0 | 422 | 0.3117 | 0.8911 | 0.8910 | |
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| 0.1129 | 3.0 | 633 | 0.4066 | 0.8886 | 0.8874 | |
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| 0.0459 | 4.0 | 844 | 0.4923 | 0.8896 | 0.8886 | |
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| 0.0275 | 5.0 | 1055 | 0.4905 | 0.8891 | 0.8886 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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