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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-mae |
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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-mae |
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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: 0.2343 |
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- Mse: 0.0824 |
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- Mae: 0.2338 |
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- Pearson Corr: 0.2477 |
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- Spearman Corr: 0.1374 |
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- Cosine Sim: 0.9022 |
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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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| 0.2846 | 1.0 | 21 | 0.2617 | 0.1153 | 0.2610 | 0.1327 | 0.0936 | 0.9053 | |
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| 0.2728 | 2.0 | 42 | 0.2310 | 0.0886 | 0.2304 | 0.0188 | 0.0316 | 0.8994 | |
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| 0.2511 | 3.0 | 63 | 0.2282 | 0.0847 | 0.2276 | 0.1716 | 0.1111 | 0.9058 | |
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| 0.2253 | 4.0 | 84 | 0.2333 | 0.0864 | 0.2329 | 0.1906 | 0.1191 | 0.9041 | |
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| 0.1993 | 5.0 | 105 | 0.2329 | 0.0822 | 0.2326 | 0.2299 | 0.1213 | 0.9016 | |
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| 0.1845 | 6.0 | 126 | 0.2357 | 0.0829 | 0.2353 | 0.2268 | 0.1254 | 0.9017 | |
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| 0.165 | 7.0 | 147 | 0.2343 | 0.0824 | 0.2338 | 0.2477 | 0.1374 | 0.9022 | |
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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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