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---
library_name: peft
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- base_model:adapter:bert-base-multilingual-cased
- lora
- transformers
model-index:
- name: BERT
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. -->
# BERT
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9472
## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.5892 | 0.0674 | 100 | 1.9698 |
| 2.2573 | 0.1347 | 200 | 2.0053 |
| 2.1211 | 0.2021 | 300 | 1.9714 |
| 2.1551 | 0.2695 | 400 | 1.9574 |
| 2.181 | 0.3368 | 500 | 1.9433 |
| 2.1707 | 0.4042 | 600 | 1.9536 |
| 2.1463 | 0.4715 | 700 | 1.9302 |
| 2.1451 | 0.5389 | 800 | 1.9041 |
| 2.1099 | 0.6063 | 900 | 1.9010 |
| 2.1178 | 0.6736 | 1000 | 1.9308 |
| 2.1292 | 0.7410 | 1100 | 1.9336 |
| 2.1285 | 0.8084 | 1200 | 1.8931 |
| 2.0634 | 0.8757 | 1300 | 1.9067 |
| 2.1118 | 0.9431 | 1400 | 1.9244 |
| 2.0807 | 1.0101 | 1500 | 1.8401 |
| 2.0402 | 1.0775 | 1600 | 1.8851 |
| 2.1129 | 1.1448 | 1700 | 1.8613 |
| 2.0707 | 1.2122 | 1800 | 1.9472 |
### Framework versions
- PEFT 0.16.0
- Transformers 4.53.2
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2 |