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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: 0.8354 |
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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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| 2.3149 | 1.0 | 3805 | 1.9892 | |
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| 1.2456 | 2.0 | 7610 | 1.1899 | |
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| 0.9588 | 3.0 | 11415 | 0.9585 | |
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| 0.8487 | 4.0 | 15220 | 0.8958 | |
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| 0.7874 | 5.0 | 19025 | 0.8803 | |
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| 0.7452 | 6.0 | 22830 | 0.8615 | |
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| 0.703 | 7.0 | 26635 | 0.8594 | |
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| 0.706 | 8.0 | 30440 | 0.8418 | |
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| 0.681 | 9.0 | 34245 | 0.8509 | |
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| 0.6653 | 10.0 | 38050 | 0.8445 | |
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| 0.6728 | 11.0 | 41855 | 0.8354 | |
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| 0.6226 | 12.0 | 45660 | 0.8583 | |
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| 0.6599 | 13.0 | 49465 | 0.8481 | |
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| 0.6375 | 14.0 | 53270 | 0.8592 | |
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| 0.64 | 15.0 | 57075 | 0.8599 | |
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| 0.644 | 16.0 | 60880 | 0.8704 | |
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| 0.5926 | 17.0 | 64685 | 0.8955 | |
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| 0.6346 | 18.0 | 68490 | 0.8906 | |
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| 0.6127 | 19.0 | 72295 | 0.9010 | |
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| 0.6051 | 20.0 | 76100 | 0.8887 | |
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| 0.6311 | 21.0 | 79905 | 0.8976 | |
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| 0.6386 | 22.0 | 83710 | 0.8875 | |
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| 0.606 | 23.0 | 87515 | 0.8969 | |
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| 0.6063 | 24.0 | 91320 | 0.9097 | |
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| 0.595 | 25.0 | 95125 | 0.9169 | |
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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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