---
license: apache-2.0
base_model: distilbert/distilbert-base-multilingual-cased
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-multilingual-cased_regression_finetuned_ptt
  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. -->

# distilbert-base-multilingual-cased_regression_finetuned_ptt

This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8809
- Mse: 1.8809
- Mae: 1.0160
- Rmse: 1.3715
- Mape: inf
- R Squared: 0.0000

## 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: 3e-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: cosine
- lr_scheduler_warmup_steps: 206
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Mse    | Mae    | Rmse   | Mape | R Squared |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:----:|:---------:|
| 1.9028        | 1.0   | 2062  | 1.8809          | 1.8809 | 1.0147 | 1.3715 | inf  | 0.0000    |
| 1.9381        | 2.0   | 4124  | 1.8831          | 1.8831 | 1.0177 | 1.3723 | inf  | -0.0011   |
| 1.8691        | 3.0   | 6186  | 1.8809          | 1.8809 | 1.0160 | 1.3715 | inf  | 0.0000    |
| 1.7741        | 4.0   | 8248  | 1.8809          | 1.8809 | 1.0153 | 1.3715 | inf  | 0.0000    |
| 1.6734        | 5.0   | 10310 | 1.8809          | 1.8809 | 1.0143 | 1.3715 | inf  | 0.0000    |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2