---
language:
- nl
license: apache-2.0
base_model: bert-base-uncased
tags:
- abc
- generated_from_trainer
datasets:
- stsb_multi_mt
model-index:
- name: bert-base-uncased-FinedTuned
  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-base-uncased-FinedTuned

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the stsb_multi_mt dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7197
- Pearson: 0.2346
- Mse: 2.7197

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 12000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Pearson | Mse    |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|:------:|
| 0.051         | 5.5556  | 1000  | 2.8182          | 0.2432  | 2.8182 |
| 0.0623        | 11.1111 | 2000  | 2.8367          | 0.2164  | 2.8367 |
| 0.0471        | 16.6667 | 3000  | 2.7305          | 0.2126  | 2.7305 |
| 0.0357        | 22.2222 | 4000  | 2.6918          | 0.2324  | 2.6918 |
| 0.032         | 27.7778 | 5000  | 2.7902          | 0.2379  | 2.7902 |
| 0.0793        | 33.3333 | 6000  | 2.7368          | 0.2480  | 2.7368 |
| 0.0775        | 38.8889 | 7000  | 2.6499          | 0.2382  | 2.6499 |
| 0.0728        | 44.4444 | 8000  | 2.6974          | 0.2368  | 2.6974 |
| 0.0596        | 50.0    | 9000  | 2.7313          | 0.2302  | 2.7313 |
| 0.1012        | 55.5556 | 10000 | 2.7291          | 0.2332  | 2.7291 |
| 0.0644        | 61.1111 | 11000 | 2.7338          | 0.2315  | 2.7338 |
| 0.1595        | 66.6667 | 12000 | 2.7197          | 0.2346  | 2.7197 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1