---
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