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---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: MBERTbase_REDv2
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. -->
# MBERTbase_REDv2
This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3320
- F1: 0.5326
- Roc Auc: 0.7058
- Accuracy: 0.4383
## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log | 1.0 | 64 | 0.4206 | 0.0 | 0.5 | 0.0 |
| No log | 2.0 | 128 | 0.3876 | 0.0901 | 0.5328 | 0.0589 |
| No log | 3.0 | 192 | 0.3599 | 0.2983 | 0.5993 | 0.2081 |
| No log | 4.0 | 256 | 0.3434 | 0.3808 | 0.6365 | 0.2965 |
| No log | 5.0 | 320 | 0.3360 | 0.4182 | 0.6474 | 0.3204 |
| No log | 6.0 | 384 | 0.3267 | 0.4638 | 0.6703 | 0.3646 |
| No log | 7.0 | 448 | 0.3259 | 0.5033 | 0.6945 | 0.3959 |
| 0.3376 | 8.0 | 512 | 0.3226 | 0.5140 | 0.6978 | 0.4217 |
| 0.3376 | 9.0 | 576 | 0.3248 | 0.5099 | 0.6959 | 0.4199 |
| 0.3376 | 10.0 | 640 | 0.3252 | 0.5230 | 0.6988 | 0.4162 |
| 0.3376 | 11.0 | 704 | 0.3258 | 0.5211 | 0.7027 | 0.4217 |
| 0.3376 | 12.0 | 768 | 0.3308 | 0.5214 | 0.6998 | 0.4309 |
| 0.3376 | 13.0 | 832 | 0.3304 | 0.5305 | 0.7052 | 0.4383 |
| 0.3376 | 14.0 | 896 | 0.3318 | 0.5297 | 0.7054 | 0.4309 |
| 0.3376 | 15.0 | 960 | 0.3320 | 0.5326 | 0.7058 | 0.4383 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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