---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: bert-reg-crossencoder-mae
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert-reg-crossencoder-mae

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2200
- Mse: 0.0781
- Mae: 0.2200
- Pearson Corr: 0.3461
- Spearman Corr: 0.3129
- Cosine Sim: 0.9050

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------------:|:-------------:|:----------:|
| 0.2886        | 1.0   | 41   | 0.2213          | 0.0742 | 0.2213 | 0.0650       | 0.0604        | 0.9037     |
| 0.2582        | 2.0   | 82   | 0.2223          | 0.0714 | 0.2223 | 0.1319       | 0.1417        | 0.9052     |
| 0.2615        | 3.0   | 123  | 0.2094          | 0.0670 | 0.2094 | 0.2859       | 0.2753        | 0.9113     |
| 0.2247        | 4.0   | 164  | 0.2152          | 0.0733 | 0.2152 | 0.3126       | 0.2705        | 0.9075     |
| 0.1942        | 5.0   | 205  | 0.2363          | 0.0890 | 0.2363 | 0.3631       | 0.3424        | 0.9112     |
| 0.1758        | 6.0   | 246  | 0.2193          | 0.0776 | 0.2193 | 0.3528       | 0.3247        | 0.9106     |
| 0.166         | 7.0   | 287  | 0.2200          | 0.0781 | 0.2200 | 0.3461       | 0.3129        | 0.9050     |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1