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--- |
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license: apache-2.0 |
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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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- accuracy |
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- f1 |
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model-index: |
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- name: distilbert-base-uncased_allagree3 |
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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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args: sentences_allagree |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9778761061946902 |
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- name: F1 |
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type: f1 |
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value: 0.9780006392634297 |
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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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# distilbert-base-uncased_allagree3 |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-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: 0.0937 |
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- Accuracy: 0.9779 |
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- F1: 0.9780 |
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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: 32 |
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- eval_batch_size: 32 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.6418 | 1.0 | 57 | 0.3340 | 0.8805 | 0.8768 | |
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| 0.1821 | 2.0 | 114 | 0.1088 | 0.9690 | 0.9691 | |
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| 0.0795 | 3.0 | 171 | 0.0822 | 0.9823 | 0.9823 | |
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| 0.0385 | 4.0 | 228 | 0.0939 | 0.9646 | 0.9646 | |
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| 0.0218 | 5.0 | 285 | 0.1151 | 0.9735 | 0.9737 | |
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| 0.0149 | 6.0 | 342 | 0.1126 | 0.9690 | 0.9694 | |
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| 0.006 | 7.0 | 399 | 0.0989 | 0.9779 | 0.9780 | |
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| 0.0093 | 8.0 | 456 | 0.1009 | 0.9779 | 0.9780 | |
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| 0.0063 | 9.0 | 513 | 0.0899 | 0.9779 | 0.9780 | |
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| 0.0039 | 10.0 | 570 | 0.0937 | 0.9779 | 0.9780 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.11.0+cpu |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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