metadata
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: []
MBERT_uncased_CrossEntropyLoss_adalora
This model is a fine-tuned version of 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