---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: bert-reg-biencoder-cosine_embedding
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-reg-biencoder-cosine_embedding

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4608
- Mse: 0.2163
- Mae: 0.3729
- Pearson Corr: 0.1820
- Spearman Corr: 0.1619
- Cosine Sim: 0.6941

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    | Mae    | Pearson Corr | Spearman Corr | Cosine Sim |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------------:|:-------------:|:----------:|
| 0.5366        | 1.0   | 21   | 0.5212          | 0.1367 | 0.2918 | 0.1078       | 0.1049        | 0.9047     |
| 0.5294        | 2.0   | 42   | 0.5061          | 0.0996 | 0.2390 | 0.1385       | 0.1515        | 0.9048     |
| 0.4811        | 3.0   | 63   | 0.4862          | 0.0855 | 0.2381 | 0.1325       | 0.0899        | 0.8857     |
| 0.4292        | 4.0   | 84   | 0.4494          | 0.1511 | 0.3202 | 0.2155       | 0.1778        | 0.7872     |
| 0.3672        | 5.0   | 105  | 0.4513          | 0.1470 | 0.3067 | 0.2206       | 0.1849        | 0.7980     |
| 0.3259        | 6.0   | 126  | 0.4644          | 0.2209 | 0.3901 | 0.1864       | 0.1662        | 0.6696     |
| 0.2866        | 7.0   | 147  | 0.4608          | 0.2163 | 0.3729 | 0.1820       | 0.1619        | 0.6941     |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0