pytorch tensorboard wav2vec2 automatic-speech-recognition transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: xls-r-300m-bemba-10hrs
  results: []
---

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# xls-r-300m-bemba-10hrs

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3022
- Wer: 0.3976

## 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: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.4544        | 1.07  | 400  | 0.4912          | 0.6813 |
| 0.662         | 2.14  | 800  | 0.3667          | 0.5690 |
| 0.4601        | 3.22  | 1200 | 0.2792          | 0.4819 |
| 0.3816        | 4.29  | 1600 | 0.2828          | 0.4608 |
| 0.3012        | 5.36  | 2000 | 0.2881          | 0.4651 |
| 0.2427        | 6.43  | 2400 | 0.2758          | 0.4219 |
| 0.1888        | 7.51  | 2800 | 0.2743          | 0.4094 |
| 0.1559        | 8.58  | 3200 | 0.2893          | 0.4021 |
| 0.1203        | 9.65  | 3600 | 0.3022          | 0.3976 |


### Framework versions

- Transformers 4.19.0.dev0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1
