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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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model-index: |
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- name: TenaliAI-FinTech-v1 |
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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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# TenaliAI-FinTech-v1 |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8315 |
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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: 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: 25 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 2.3436 | 1.0 | 3809 | 1.9815 | |
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| 1.2453 | 2.0 | 7618 | 1.1621 | |
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| 0.9853 | 3.0 | 11427 | 0.9375 | |
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| 0.8483 | 4.0 | 15236 | 0.9018 | |
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| 0.8195 | 5.0 | 19045 | 0.8538 | |
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| 0.7579 | 6.0 | 22854 | 0.8540 | |
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| 0.7123 | 7.0 | 26663 | 0.8397 | |
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| 0.7064 | 8.0 | 30472 | 0.8405 | |
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| 0.6987 | 9.0 | 34281 | 0.8315 | |
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| 0.676 | 10.0 | 38090 | 0.8530 | |
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| 0.6566 | 11.0 | 41899 | 0.8504 | |
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| 0.6411 | 12.0 | 45708 | 0.8501 | |
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| 0.6432 | 13.0 | 49517 | 0.8545 | |
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| 0.6483 | 14.0 | 53326 | 0.8624 | |
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| 0.6447 | 15.0 | 57135 | 0.8635 | |
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| 0.6077 | 16.0 | 60944 | 0.8782 | |
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| 0.6208 | 17.0 | 64753 | 0.8925 | |
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| 0.624 | 18.0 | 68562 | 0.8834 | |
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| 0.6298 | 19.0 | 72371 | 0.9000 | |
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| 0.6488 | 20.0 | 76180 | 0.8922 | |
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| 0.6019 | 21.0 | 79989 | 0.9025 | |
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| 0.6412 | 22.0 | 83798 | 0.8963 | |
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| 0.6078 | 23.0 | 87607 | 0.9045 | |
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| 0.6163 | 24.0 | 91416 | 0.8898 | |
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| 0.6275 | 25.0 | 95225 | 0.9036 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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