---
library_name: peft
license: apache-2.0
base_model: google-bert/bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: MBERT_uncased_CrossEntropyLoss_adalora
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# MBERT_uncased_CrossEntropyLoss_adalora

This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.67
- F1: 0.8005
- Precision: 0.7118
- Recall: 0.9144
- Roc Auc: 0.4717
- Loss: 0.6634

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Accuracy | F1     | Precision | Recall | Roc Auc | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:------:|:---------:|:------:|:-------:|:---------------:|
| No log        | 0.992 | 31   | 0.636    | 0.7745 | 0.7022    | 0.8633 | 0.4516  | 0.6726          |
| No log        | 1.984 | 62   | 0.662    | 0.7947 | 0.7093    | 0.9033 | 0.4662  | 0.6656          |
| No log        | 2.976 | 93   | 0.67     | 0.8005 | 0.7118    | 0.9144 | 0.4717  | 0.6634          |


### Framework versions

- PEFT 0.13.3.dev0
- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3