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: 0.5977
- Precision: 0.6463
- Recall: 0.6078
- F1: 0.6264
- Accuracy: 0.8835
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: 16
- eval_batch_size: 16
- 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 | 145 | 0.6113 | 0.6550 | 0.5854 | 0.6182 | 0.8735 |
| No log | 2.0 | 290 | 0.6457 | 0.6270 | 0.5659 | 0.5949 | 0.8705 |
| No log | 3.0 | 435 | 0.5977 | 0.6463 | 0.6078 | 0.6264 | 0.8835 |
| 0.1409 | 4.0 | 580 | 0.6095 | 0.6752 | 0.6449 | 0.6597 | 0.8865 |
| 0.1409 | 5.0 | 725 | 0.6566 | 0.6680 | 0.6380 | 0.6527 | 0.8851 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3