---
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: W2V2-Bert_DigitalUmuganda_Afrivoice_Shona_1hr_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. -->

# W2V2-Bert_DigitalUmuganda_Afrivoice_Shona_1hr_v2

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: 0.4556
- Model Preparation Time: 0.0127
- Wer: 0.3692
- Cer: 0.0718

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Model Preparation Time | Wer    | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:----------------------:|:------:|:------:|
| 7.2051        | 0.9778  | 22   | 6.1914          | 0.0127                 | 1.0    | 0.9176 |
| 4.1072        | 2.0     | 45   | 3.1571          | 0.0127                 | 1.0    | 0.9905 |
| 3.0778        | 2.9778  | 67   | 2.8928          | 0.0127                 | 1.0    | 0.9418 |
| 2.6835        | 4.0     | 90   | 2.5263          | 0.0127                 | 1.0    | 0.7968 |
| 2.0498        | 4.9778  | 112  | 1.1299          | 0.0127                 | 0.9935 | 0.3234 |
| 0.6781        | 6.0     | 135  | 0.4324          | 0.0127                 | 0.5731 | 0.0952 |
| 0.3809        | 6.9778  | 157  | 0.3307          | 0.0127                 | 0.4004 | 0.0667 |
| 0.2728        | 8.0     | 180  | 0.2900          | 0.0127                 | 0.3482 | 0.0571 |
| 0.2301        | 8.9778  | 202  | 0.2700          | 0.0127                 | 0.3382 | 0.0549 |
| 0.1725        | 10.0    | 225  | 0.2791          | 0.0127                 | 0.3510 | 0.0541 |
| 0.1417        | 10.9778 | 247  | 0.2745          | 0.0127                 | 0.3643 | 0.0551 |
| 0.1158        | 12.0    | 270  | 0.3095          | 0.0127                 | 0.3256 | 0.0534 |
| 0.1125        | 12.9778 | 292  | 0.2983          | 0.0127                 | 0.3407 | 0.0555 |
| 0.0854        | 14.0    | 315  | 0.3183          | 0.0127                 | 0.3505 | 0.0540 |
| 0.078         | 14.9778 | 337  | 0.3576          | 0.0127                 | 0.3409 | 0.0549 |
| 0.0661        | 16.0    | 360  | 0.3444          | 0.0127                 | 0.3550 | 0.0567 |
| 0.0736        | 16.9778 | 382  | 0.3750          | 0.0127                 | 0.3570 | 0.0595 |
| 0.0584        | 18.0    | 405  | 0.3570          | 0.0127                 | 0.3738 | 0.0583 |
| 0.0503        | 18.9778 | 427  | 0.4068          | 0.0127                 | 0.3740 | 0.0612 |
| 0.0498        | 20.0    | 450  | 0.3769          | 0.0127                 | 0.3545 | 0.0581 |
| 0.0549        | 20.9778 | 472  | 0.3819          | 0.0127                 | 0.3620 | 0.0574 |
| 0.049         | 22.0    | 495  | 0.3945          | 0.0127                 | 0.3632 | 0.0582 |


### Framework versions

- Transformers 4.44.1
- Pytorch 2.2.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1