---
base_model: old_models/LaBSE/0_Transformer
tags:
- generated_from_trainer
model-index:
- name: bert_labse-finetuning-unhealthyConv-dropout005-epochs-10
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert_labse-finetuning-unhealthyConv-dropout005-epochs-10

This model is a fine-tuned version of [old_models/LaBSE/0_Transformer](https://huggingface.co/old_models/LaBSE/0_Transformer) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7820
- Mse: 0.7820
- Rmse: 0.8843
- Mae: 0.4988
- R2: 0.8587

## 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
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Mse    | Rmse   | Mae    | R2     |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|
| 1.5159        | 1.0   | 3389  | 1.2618          | 1.2618 | 1.1233 | 0.7882 | 0.7720 |
| 1.0247        | 2.0   | 6778  | 1.1135          | 1.1135 | 1.0552 | 0.7067 | 0.7988 |
| 0.7849        | 3.0   | 10167 | 1.1353          | 1.1353 | 1.0655 | 0.7289 | 0.7949 |
| 0.6271        | 4.0   | 13556 | 0.9255          | 0.9255 | 0.9620 | 0.6331 | 0.8328 |
| 0.5029        | 5.0   | 16945 | 0.9135          | 0.9135 | 0.9558 | 0.6148 | 0.8349 |
| 0.3947        | 6.0   | 20334 | 0.8166          | 0.8166 | 0.9036 | 0.5446 | 0.8525 |
| 0.3264        | 7.0   | 23723 | 0.8280          | 0.8280 | 0.9099 | 0.5552 | 0.8504 |
| 0.2774        | 8.0   | 27112 | 0.8125          | 0.8125 | 0.9014 | 0.5408 | 0.8532 |
| 0.2245        | 9.0   | 30501 | 0.7870          | 0.7870 | 0.8871 | 0.5034 | 0.8578 |
| 0.2028        | 10.0  | 33890 | 0.7820          | 0.7820 | 0.8843 | 0.4988 | 0.8587 |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3