---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: bert-base-multilingual-cased-kin
  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-kin

This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1279
- Accuracy: 0.7783
- F1 Binary: 0.4346
- Precision: 0.3214
- Recall: 0.6711

## 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: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 36
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Binary | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:---------:|:------:|
| No log        | 1.0   | 184  | 0.1324          | 0.6656   | 0.3682    | 0.2422    | 0.7674 |
| No log        | 2.0   | 368  | 0.1275          | 0.7804   | 0.4208    | 0.3163    | 0.6283 |
| 0.1113        | 3.0   | 552  | 0.1123          | 0.7753   | 0.4173    | 0.3110    | 0.6337 |
| 0.1113        | 4.0   | 736  | 0.1279          | 0.7783   | 0.4346    | 0.3214    | 0.6711 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0