---
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
datasets:
- fleurs
model-index:
- name: w2v2-bert-Wolof-5-hours-Google-Fleurs-dataset
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# w2v2-bert-Wolof-5-hours-Google-Fleurs-dataset

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the fleurs dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.4897
- eval_wer: 0.4518
- eval_cer: 0.1503
- eval_runtime: 47.5107
- eval_samples_per_second: 7.809
- eval_steps_per_second: 0.989
- epoch: 39.02
- step: 1600

## 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

### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu118
- Datasets 2.17.0
- Tokenizers 0.15.2