metadata
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: multibertfinetuned1107
results: []
multibertfinetuned1107
This model is a fine-tuned version of bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4896
- Precision: 0.6282
- Recall: 0.5688
- F1: 0.5970
- Accuracy: 0.8756
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: 32
- eval_batch_size: 32
- seed: 42
- 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 73 | 0.5149 | 0.5414 | 0.4527 | 0.4931 | 0.8510 |
| No log | 2.0 | 146 | 0.6092 | 0.57 | 0.5005 | 0.5330 | 0.8464 |
| No log | 3.0 | 219 | 0.4896 | 0.6282 | 0.5688 | 0.5970 | 0.8756 |
| No log | 4.0 | 292 | 0.5196 | 0.6420 | 0.6176 | 0.6295 | 0.8764 |
| No log | 5.0 | 365 | 0.5270 | 0.6479 | 0.6176 | 0.6324 | 0.8786 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3