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--- |
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library_name: transformers |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: bert-reg-biencoder-mse |
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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-reg-biencoder-mse |
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0817 |
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- Mse: 0.0812 |
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- Mae: 0.2278 |
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- Pearson Corr: 0.2835 |
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- Spearman Corr: 0.2331 |
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- Cosine Sim: 0.9097 |
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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: 32 |
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- eval_batch_size: 32 |
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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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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 7 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | Pearson Corr | Spearman Corr | Cosine Sim | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------------:|:-------------:|:----------:| |
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| 0.1219 | 1.0 | 21 | 0.1124 | 0.1117 | 0.2560 | 0.1406 | 0.0993 | 0.9055 | |
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| 0.1017 | 2.0 | 42 | 0.0838 | 0.0833 | 0.2248 | 0.1312 | 0.1239 | 0.9045 | |
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| 0.0872 | 3.0 | 63 | 0.0778 | 0.0775 | 0.2205 | 0.2520 | 0.1374 | 0.9097 | |
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| 0.0694 | 4.0 | 84 | 0.0860 | 0.0856 | 0.2328 | 0.1923 | 0.1456 | 0.9037 | |
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| 0.0533 | 5.0 | 105 | 0.0958 | 0.0951 | 0.2418 | 0.3089 | 0.2252 | 0.9132 | |
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| 0.0478 | 6.0 | 126 | 0.0782 | 0.0778 | 0.2216 | 0.2913 | 0.2325 | 0.9096 | |
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| 0.0385 | 7.0 | 147 | 0.0817 | 0.0812 | 0.2278 | 0.2835 | 0.2331 | 0.9097 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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