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--- |
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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: 0.1134 |
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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: 8 |
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- eval_batch_size: 8 |
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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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| No log | 1.0 | 224 | 2.5812 | |
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| No log | 2.0 | 448 | 1.2454 | |
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| 2.5217 | 3.0 | 672 | 0.4337 | |
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| 2.5217 | 4.0 | 896 | 0.1572 | |
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| 0.4296 | 5.0 | 1120 | 0.1191 | |
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| 0.4296 | 6.0 | 1344 | 0.1208 | |
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| 0.0629 | 7.0 | 1568 | 0.1140 | |
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| 0.0629 | 8.0 | 1792 | 0.1212 | |
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| 0.0254 | 9.0 | 2016 | 0.1215 | |
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| 0.0254 | 10.0 | 2240 | 0.1213 | |
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| 0.0254 | 11.0 | 2464 | 0.1136 | |
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| 0.0118 | 12.0 | 2688 | 0.1134 | |
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| 0.0118 | 13.0 | 2912 | 0.1161 | |
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| 0.0092 | 14.0 | 3136 | 0.1191 | |
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| 0.0092 | 15.0 | 3360 | 0.1305 | |
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| 0.0056 | 16.0 | 3584 | 0.1332 | |
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| 0.0056 | 17.0 | 3808 | 0.1343 | |
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| 0.0055 | 18.0 | 4032 | 0.1362 | |
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| 0.0055 | 19.0 | 4256 | 0.1362 | |
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| 0.0055 | 20.0 | 4480 | 0.1450 | |
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| 0.0037 | 21.0 | 4704 | 0.1421 | |
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| 0.0037 | 22.0 | 4928 | 0.1460 | |
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| 0.003 | 23.0 | 5152 | 0.1472 | |
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| 0.003 | 24.0 | 5376 | 0.1428 | |
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| 0.0026 | 25.0 | 5600 | 0.1493 | |
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### Framework versions |
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- Transformers 4.43.4 |
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- Pytorch 2.4.0 |
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- Tokenizers 0.19.1 |
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