---
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: 0.6334
- Mse: 0.6334
- Mae: 0.4908

## 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: 891
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Mse    | Mae    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 1.055         | 1.0   | 8917  | 0.9565          | 0.9565 | 0.6907 |
| 0.8048        | 2.0   | 17834 | 0.7746          | 0.7746 | 0.6010 |
| 0.6171        | 3.0   | 26751 | 0.7066          | 0.7066 | 0.5555 |
| 0.5647        | 4.0   | 35668 | 0.6739          | 0.6739 | 0.5297 |
| 0.5468        | 5.0   | 44585 | 0.6283          | 0.6283 | 0.5066 |
| 0.5439        | 6.0   | 53502 | 0.6335          | 0.6335 | 0.5029 |
| 0.4582        | 7.0   | 62419 | 0.6354          | 0.6354 | 0.4968 |
| 0.4479        | 8.0   | 71336 | 0.6334          | 0.6334 | 0.4908 |
| 0.4195        | 9.0   | 80253 | 0.6403          | 0.6403 | 0.4919 |
| 0.4137        | 10.0  | 89170 | 0.6401          | 0.6401 | 0.4922 |


### Framework versions

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