
<!-- 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. -->

# mbert_ver_2_task_1A

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3826
- Accuracy: 0.9003
- F1: 0.8999
- Precision: 0.8998
- Recall: 0.9003

## 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: 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: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.2827        | 1.0   | 3523  | 0.2734          | 0.8841   | 0.8826 | 0.8921    | 0.8841 |
| 0.2242        | 2.0   | 7046  | 0.2799          | 0.8949   | 0.8957 | 0.8972    | 0.8949 |
| 0.1658        | 3.0   | 10569 | 0.3093          | 0.9003   | 0.9000 | 0.9004    | 0.9003 |
| 0.1404        | 4.0   | 14092 | 0.3826          | 0.9003   | 0.8999 | 0.8998    | 0.9003 |


### Framework versions

- Transformers 4.30.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "model-index": [{"name": "mbert_ver_2_task_1A", "results": []}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us