---
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-bert-r-Wolof-5-hours-kallaama-dataset
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/asr-africa-research-team/ASR%20Africa/runs/sk42is0e)
# w2v2-bert-r-Wolof-5-hours-kallaama-dataset

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3781
- Wer: 0.5466
- Cer: 0.2727

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 2.299         | 5.9480  | 400  | 1.9903          | 0.8333 | 0.4075 |
| 1.721         | 11.8959 | 800  | 1.7083          | 0.7612 | 0.4171 |
| 1.3926        | 17.8439 | 1200 | 1.6886          | 0.6504 | 0.3240 |
| 1.1457        | 23.7918 | 1600 | 1.5706          | 0.6120 | 0.3168 |
| 0.9292        | 29.7398 | 2000 | 1.7518          | 0.5761 | 0.2857 |
| 0.7281        | 35.6877 | 2400 | 1.8207          | 0.5500 | 0.2746 |
| 0.5193        | 41.6357 | 2800 | 1.8834          | 0.5599 | 0.2794 |
| 0.3446        | 47.5836 | 3200 | 2.3781          | 0.5466 | 0.2727 |


### Framework versions

- Transformers 4.44.1
- Pytorch 2.1.0+cu118
- Datasets 2.17.0
- Tokenizers 0.19.1