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---
license: apache-2.0
base_model: distilbert/distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilbert-lang-detect
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-lang-detect
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: 0.1215
- Accuracy: 0.9720
- F1: 0.9720
- Precision: 0.9720
- Recall: 0.9720
## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1022 | 1.0 | 14547 | 0.0924 | 0.9703 | 0.9703 | 0.9703 | 0.9703 |
| 0.0783 | 2.0 | 29094 | 0.0924 | 0.9704 | 0.9704 | 0.9705 | 0.9704 |
| 0.0646 | 3.0 | 43641 | 0.1096 | 0.9724 | 0.9724 | 0.9725 | 0.9724 |
| 0.053 | 4.0 | 58188 | 0.1188 | 0.9722 | 0.9722 | 0.9722 | 0.9722 |
| 0.0364 | 5.0 | 72735 | 0.1215 | 0.9720 | 0.9720 | 0.9720 | 0.9720 |
### Framework versions
- Transformers 4.39.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.0
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