| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| model-index: |
| - name: nli_mbert |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # nli_mbert |
| |
| 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: 1.6569 |
| - Accuracy: 0.7419 |
| - Precision: 0.7419 |
| - Recall: 0.7419 |
| - F1 Score: 0.7426 |
| |
| ## 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: 3e-06 |
| - train_batch_size: 1 |
| - eval_batch_size: 1 |
| - seed: 101 |
| - 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 | Accuracy | Precision | Recall | F1 Score | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:--------:| |
| | 1.403 | 1.0 | 10330 | 1.3860 | 0.7128 | 0.7128 | 0.7128 | 0.7142 | |
| | 1.3213 | 2.0 | 20660 | 1.3367 | 0.7365 | 0.7365 | 0.7365 | 0.7371 | |
| | 1.1611 | 3.0 | 30990 | 1.4699 | 0.7396 | 0.7396 | 0.7396 | 0.7406 | |
| | 1.0222 | 4.0 | 41320 | 1.6050 | 0.7374 | 0.7374 | 0.7374 | 0.7383 | |
| | 0.9008 | 5.0 | 51650 | 1.6569 | 0.7419 | 0.7419 | 0.7419 | 0.7426 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.30.0.dev0 |
| - Pytorch 2.0.0 |
| - Datasets 2.1.0 |
| - Tokenizers 0.13.3 |
| |
