---
license: apache-2.0
base_model: distilbert/distilbert-base-multilingual-cased
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-multilingual-cased_regression_finetuned_dcard
  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_dcard

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: 0.0004
- Mse: 0.0004
- Mae: 0.0153

## 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
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    | Mae    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| No log        | 1.0   | 5    | 0.1120          | 0.1120 | 0.3246 |
| No log        | 2.0   | 10   | 0.0117          | 0.0117 | 0.0966 |
| No log        | 3.0   | 15   | 0.0048          | 0.0048 | 0.0602 |
| No log        | 4.0   | 20   | 0.0029          | 0.0029 | 0.0492 |
| No log        | 5.0   | 25   | 0.0016          | 0.0016 | 0.0328 |
| No log        | 6.0   | 30   | 0.0005          | 0.0005 | 0.0173 |
| No log        | 7.0   | 35   | 0.0004          | 0.0004 | 0.0177 |
| No log        | 8.0   | 40   | 0.0003          | 0.0003 | 0.0157 |
| No log        | 9.0   | 45   | 0.0004          | 0.0004 | 0.0154 |
| 0.0654        | 10.0  | 50   | 0.0004          | 0.0004 | 0.0153 |


### Framework versions

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