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README.md ADDED
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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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+
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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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+
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+ # bert-reg-biencoder-mae
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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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