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---
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: 0.6568
- Mse: 0.6568
- Mae: 0.5036
- Rmse: 0.8104
- Mape: inf
- R Squared: 0.5925
## 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 | Rmse | Mape | R Squared |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:----:|:---------:|
| 1.0667 | 1.0 | 8917 | 0.9488 | 0.9488 | 0.6910 | 0.9741 | inf | 0.4113 |
| 0.8502 | 2.0 | 17834 | 0.7789 | 0.7789 | 0.6072 | 0.8825 | inf | 0.5167 |
| 0.6093 | 3.0 | 26751 | 0.7659 | 0.7659 | 0.5919 | 0.8751 | inf | 0.5248 |
| 0.5891 | 4.0 | 35668 | 0.7029 | 0.7029 | 0.5537 | 0.8384 | inf | 0.5639 |
| 0.5542 | 5.0 | 44585 | 0.6521 | 0.6521 | 0.5156 | 0.8075 | inf | 0.5954 |
| 0.5475 | 6.0 | 53502 | 0.6414 | 0.6414 | 0.5087 | 0.8009 | inf | 0.6020 |
| 0.4619 | 7.0 | 62419 | 0.6389 | 0.6389 | 0.5015 | 0.7993 | inf | 0.6036 |
| 0.4368 | 8.0 | 71336 | 0.6471 | 0.6471 | 0.5014 | 0.8044 | inf | 0.5985 |
| 0.4106 | 9.0 | 80253 | 0.6568 | 0.6568 | 0.5036 | 0.8104 | inf | 0.5925 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2
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