---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
model-index:
- name: bert-base-multilingual-cased-finetuned-newqa1
  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. -->

# bert-base-multilingual-cased-finetuned-newqa1

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: 3.6464

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 66   | 2.4436          |
| No log        | 2.0   | 132  | 2.9332          |
| No log        | 3.0   | 198  | 2.8448          |
| No log        | 4.0   | 264  | 3.1388          |
| No log        | 5.0   | 330  | 3.3338          |
| No log        | 6.0   | 396  | 3.3124          |
| No log        | 7.0   | 462  | 3.2653          |
| 0.5371        | 8.0   | 528  | 3.4633          |
| 0.5371        | 9.0   | 594  | 3.5907          |
| 0.5371        | 10.0  | 660  | 3.5120          |
| 0.5371        | 11.0  | 726  | 3.6371          |
| 0.5371        | 12.0  | 792  | 3.6414          |
| 0.5371        | 13.0  | 858  | 3.5953          |
| 0.5371        | 14.0  | 924  | 3.6044          |
| 0.5371        | 15.0  | 990  | 3.6464          |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3