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--- |
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license: apache-2.0 |
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base_model: distilbert-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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- accuracy |
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model-index: |
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- name: distilbert-finance |
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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_50agree |
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split: train |
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args: sentences_50agree |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7386363636363636 |
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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-finance |
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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: 0.9962 |
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- Accuracy: 0.7386 |
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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: 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: cosine |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.904 | 0.33 | 20 | 1.5959 | 0.4205 | |
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| 0.6562 | 0.66 | 40 | 1.6665 | 0.4143 | |
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| 0.539 | 0.98 | 60 | 1.6067 | 0.3936 | |
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| 0.4759 | 1.31 | 80 | 1.5079 | 0.4236 | |
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| 0.3882 | 1.64 | 100 | 1.4719 | 0.4298 | |
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| 0.3782 | 1.97 | 120 | 1.2392 | 0.4267 | |
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| 0.2729 | 2.3 | 140 | 1.0114 | 0.4928 | |
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| 0.2607 | 2.62 | 160 | 0.9514 | 0.5930 | |
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| 0.2889 | 2.95 | 180 | 0.8661 | 0.6477 | |
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| 0.181 | 3.28 | 200 | 0.7093 | 0.7417 | |
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| 0.1742 | 3.61 | 220 | 1.1042 | 0.5764 | |
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| 0.1904 | 3.93 | 240 | 0.7439 | 0.7510 | |
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| 0.1186 | 4.26 | 260 | 0.8587 | 0.7469 | |
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| 0.137 | 4.59 | 280 | 0.7408 | 0.7603 | |
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| 0.1166 | 4.92 | 300 | 1.0107 | 0.6705 | |
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| 0.0938 | 5.25 | 320 | 0.7883 | 0.7624 | |
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| 0.0881 | 5.57 | 340 | 1.0339 | 0.7056 | |
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| 0.0812 | 5.9 | 360 | 0.8409 | 0.7490 | |
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| 0.0586 | 6.23 | 380 | 0.9146 | 0.7345 | |
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| 0.0572 | 6.56 | 400 | 0.9000 | 0.7366 | |
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| 0.0527 | 6.89 | 420 | 0.9782 | 0.7335 | |
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| 0.045 | 7.21 | 440 | 1.0102 | 0.7262 | |
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| 0.0471 | 7.54 | 460 | 1.0322 | 0.7324 | |
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| 0.0508 | 7.87 | 480 | 0.9381 | 0.7448 | |
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| 0.039 | 8.2 | 500 | 0.9489 | 0.7459 | |
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| 0.0419 | 8.52 | 520 | 0.9779 | 0.7469 | |
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| 0.0256 | 8.85 | 540 | 0.9834 | 0.7407 | |
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| 0.0264 | 9.18 | 560 | 0.9963 | 0.7376 | |
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| 0.0378 | 9.51 | 580 | 0.9981 | 0.7376 | |
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| 0.0421 | 9.84 | 600 | 0.9962 | 0.7386 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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