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# bert-base-multilingual-cased-qnli-1

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the tmnam20/VieGLUE/QNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3278
- Accuracy: 0.8852

## 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: 32
- eval_batch_size: 16
- seed: 1
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3938        | 0.15  | 500  | 0.3494          | 0.8495   |
| 0.3712        | 0.31  | 1000 | 0.3266          | 0.8570   |
| 0.3837        | 0.46  | 1500 | 0.3174          | 0.8655   |
| 0.3466        | 0.61  | 2000 | 0.2957          | 0.8785   |
| 0.3084        | 0.76  | 2500 | 0.3093          | 0.8715   |
| 0.322         | 0.92  | 3000 | 0.2950          | 0.8731   |
| 0.273         | 1.07  | 3500 | 0.2872          | 0.8834   |
| 0.2628        | 1.22  | 4000 | 0.3110          | 0.8794   |
| 0.2732        | 1.37  | 4500 | 0.2910          | 0.8797   |
| 0.2592        | 1.53  | 5000 | 0.2855          | 0.8849   |
| 0.241         | 1.68  | 5500 | 0.2974          | 0.8861   |
| 0.2256        | 1.83  | 6000 | 0.2914          | 0.8850   |
| 0.2402        | 1.99  | 6500 | 0.2759          | 0.8883   |
| 0.1958        | 2.14  | 7000 | 0.3080          | 0.8880   |
| 0.1684        | 2.29  | 7500 | 0.3190          | 0.8847   |
| 0.1472        | 2.44  | 8000 | 0.3305          | 0.8871   |
| 0.1601        | 2.6   | 8500 | 0.3298          | 0.8836   |
| 0.1857        | 2.75  | 9000 | 0.3274          | 0.8847   |
| 0.1667        | 2.9   | 9500 | 0.3256          | 0.8841   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.2.0.dev20231203+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

{"language": ["en"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["tmnam20/VieGLUE"], "metrics": ["accuracy"], "base_model": "bert-base-multilingual-cased", "model-index": [{"name": "bert-base-multilingual-cased-qnli-1", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "tmnam20/VieGLUE/QNLI", "type": "tmnam20/VieGLUE", "config": "qnli", "split": "validation", "args": "qnli"}, "metrics": [{"type": "accuracy", "value": 0.885227896760022, "name": "Accuracy"}]}]}]}
transformers safetensors bert text-classification generated_from_trainer en dataset:tmnam20/VieGLUE base_model:bert-base-multilingual-cased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us