---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: wav2vec2_xls_r_300m_FLEURS_Shona_1hr_v1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: fleurs
      type: fleurs
      config: sn_zw
      split: validation
      args: sn_zw
    metrics:
    - name: Wer
      type: wer
      value: 1.0
---

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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/3qfcd7l5)
# wav2vec2_xls_r_300m_FLEURS_Shona_1hr_v1

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 12.4333
- Wer: 1.0
- Cer: 0.9978

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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 | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| No log        | 1.0   | 8    | 14.4606         | 2.7557 | 0.9555 |
| No log        | 2.0   | 16   | 14.3682         | 1.4924 | 0.9242 |
| No log        | 3.0   | 24   | 14.1641         | 1.0992 | 0.9862 |
| No log        | 4.0   | 32   | 13.8827         | 1.0229 | 0.9902 |
| No log        | 5.0   | 40   | 13.4780         | 1.0076 | 0.9925 |
| No log        | 6.0   | 48   | 12.8015         | 1.0    | 0.9976 |
| No log        | 7.0   | 56   | 11.7499         | 1.0    | 1.0    |
| No log        | 8.0   | 64   | 10.0606         | 1.0    | 1.0    |
| No log        | 9.0   | 72   | 8.2175          | 1.0    | 1.0    |
| No log        | 10.0  | 80   | 6.8124          | 1.0    | 1.0    |
| No log        | 11.0  | 88   | 5.9146          | 1.0    | 1.0    |
| No log        | 12.0  | 96   | 5.2321          | 1.0    | 1.0    |
| 10.8148       | 13.0  | 104  | 4.7869          | 1.0    | 1.0    |
| 10.8148       | 14.0  | 112  | 4.4701          | 1.0    | 1.0    |
| 10.8148       | 15.0  | 120  | 4.2285          | 1.0    | 1.0    |
| 10.8148       | 16.0  | 128  | 4.0551          | 1.0    | 1.0    |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1