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license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- recall
- f1
- accuracy
model-index:
- name: m-bert
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. -->
# m-bert
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: 0.3141
- Precison: 0.8543
- Recall: 0.8566
- F1: 0.8554
- Accuracy: 0.8594
- Jaccard: 0.7848
## 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: 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precison | Recall | F1 | Accuracy | Jaccard |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:--------:|:-------:|
| 0.4088 | 1.0 | 1513 | 0.3141 | 0.8543 | 0.8566 | 0.8554 | 0.8594 | 0.7848 |
| 0.3328 | 2.0 | 3026 | 0.3161 | 0.8685 | 0.8530 | 0.8587 | 0.8656 | 0.8018 |
| 0.2521 | 3.0 | 4539 | 0.3444 | 0.8729 | 0.8700 | 0.8714 | 0.8758 | 0.8105 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1
|