---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: multibert2809_flow
  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. -->

# multibert2809_flow

This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4534
- Precision: 0.7055
- Recall: 0.7076
- F1: 0.7066
- Accuracy: 0.8709

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 118  | 0.5021          | 0.6550    | 0.6229 | 0.6385 | 0.8414   |
| No log        | 2.0   | 236  | 0.4534          | 0.7055    | 0.7076 | 0.7066 | 0.8709   |
| No log        | 3.0   | 354  | 0.4903          | 0.7455    | 0.7237 | 0.7345 | 0.8752   |
| No log        | 4.0   | 472  | 0.5158          | 0.7488    | 0.7327 | 0.7407 | 0.8755   |
| 0.3074        | 5.0   | 590  | 0.5685          | 0.7502    | 0.7434 | 0.7468 | 0.8758   |
| 0.3074        | 6.0   | 708  | 0.5799          | 0.7612    | 0.7530 | 0.7570 | 0.8809   |
| 0.3074        | 7.0   | 826  | 0.6022          | 0.7673    | 0.7494 | 0.7582 | 0.8791   |
| 0.3074        | 8.0   | 944  | 0.6054          | 0.7663    | 0.7554 | 0.7608 | 0.8840   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3