---
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- recall
- f1
- accuracy
model-index:
- name: bert-base-multilingual-cased-finetune-claim
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-multilingual-cased-finetune-claim

This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4472
- Precison: 0.7782
- Recall: 0.7803
- F1: 0.7792
- Accuracy: 0.7891
- Jaccard: 0.5779

## 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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precison | Recall | F1     | Accuracy | Jaccard |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:--------:|:-------:|
| 0.411         | 1.0   | 1513 | 0.3212          | 0.8524   | 0.8559 | 0.8540 | 0.8578   | 0.7817  |
| 0.3154        | 2.0   | 3026 | 0.3158          | 0.8639   | 0.8630 | 0.8634 | 0.8678   | 0.7984  |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1