Model save
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README.md
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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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model.safetensors
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