---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-unpunctual-text-segmentation-v2
  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-finetuned-unpunctual-text-segmentation-v2

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0010
- Precision: 0.9989
- Recall: 0.9979
- F1: 0.9984
- Accuracy: 0.9997

## 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0047        | 1.0   | 4750  | 0.0041          | 0.9892    | 0.9966 | 0.9929 | 0.9988   |
| 0.0015        | 2.0   | 9500  | 0.0017          | 0.9983    | 0.9953 | 0.9968 | 0.9995   |
| 0.0004        | 3.0   | 14250 | 0.0010          | 0.9989    | 0.9979 | 0.9984 | 0.9997   |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3