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--- |
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license: apache-2.0 |
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base_model: google-bert/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: bert-petco-fullemailbody-ctr |
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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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# bert-petco-fullemailbody-ctr |
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0024 |
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- Mse: 0.0024 |
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- Rmse: 0.0487 |
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- Mae: 0.0369 |
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- R2: 0.3917 |
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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: 1e-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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mse | Rmse | Mae | R2 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:-------:| |
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| 0.0259 | 1.0 | 15 | 0.0045 | 0.0045 | 0.0671 | 0.0558 | -0.1551 | |
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| 0.0131 | 2.0 | 30 | 0.0042 | 0.0042 | 0.0645 | 0.0501 | -0.0669 | |
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| 0.0114 | 3.0 | 45 | 0.0037 | 0.0037 | 0.0609 | 0.0514 | 0.0488 | |
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| 0.0118 | 4.0 | 60 | 0.0033 | 0.0033 | 0.0576 | 0.0446 | 0.1471 | |
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| 0.0097 | 5.0 | 75 | 0.0036 | 0.0036 | 0.0599 | 0.0460 | 0.0790 | |
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| 0.0095 | 6.0 | 90 | 0.0037 | 0.0037 | 0.0606 | 0.0462 | 0.0568 | |
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| 0.0086 | 7.0 | 105 | 0.0040 | 0.0040 | 0.0629 | 0.0485 | -0.0177 | |
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| 0.0083 | 8.0 | 120 | 0.0026 | 0.0026 | 0.0513 | 0.0392 | 0.3232 | |
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| 0.0077 | 9.0 | 135 | 0.0035 | 0.0035 | 0.0595 | 0.0445 | 0.0915 | |
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| 0.0067 | 10.0 | 150 | 0.0037 | 0.0037 | 0.0606 | 0.0462 | 0.0561 | |
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| 0.0066 | 11.0 | 165 | 0.0025 | 0.0025 | 0.0503 | 0.0394 | 0.3499 | |
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| 0.0066 | 12.0 | 180 | 0.0034 | 0.0034 | 0.0580 | 0.0475 | 0.1355 | |
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| 0.0046 | 13.0 | 195 | 0.0024 | 0.0024 | 0.0487 | 0.0369 | 0.3917 | |
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| 0.0052 | 14.0 | 210 | 0.0035 | 0.0035 | 0.0587 | 0.0454 | 0.1137 | |
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| 0.0049 | 15.0 | 225 | 0.0032 | 0.0032 | 0.0567 | 0.0438 | 0.1753 | |
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| 0.0041 | 16.0 | 240 | 0.0034 | 0.0034 | 0.0581 | 0.0445 | 0.1321 | |
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| 0.0039 | 17.0 | 255 | 0.0030 | 0.0030 | 0.0548 | 0.0412 | 0.2277 | |
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| 0.0042 | 18.0 | 270 | 0.0036 | 0.0036 | 0.0603 | 0.0465 | 0.0676 | |
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| 0.0035 | 19.0 | 285 | 0.0036 | 0.0036 | 0.0601 | 0.0461 | 0.0719 | |
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| 0.0031 | 20.0 | 300 | 0.0033 | 0.0033 | 0.0574 | 0.0435 | 0.1548 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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