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---
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
|