---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2_xls_r_300m_BIG-C_Bemba_100hr_v1
  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. -->

# wav2vec2_xls_r_300m_BIG-C_Bemba_100hr_v1

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: 0.4735
- Model Preparation Time: 0.005
- Wer: 0.4226
- Cer: 0.1075

## 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: 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 | Model Preparation Time | Wer    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:----------------------:|:------:|:------:|
| 1.4689        | 1.0   | 1549  | inf             | 0.005                  | 0.4875 | 0.1241 |
| 0.5854        | 2.0   | 3098  | inf             | 0.005                  | 0.4906 | 0.1216 |
| 0.5464        | 3.0   | 4647  | inf             | 0.005                  | 0.4519 | 0.1163 |
| 0.5213        | 4.0   | 6196  | inf             | 0.005                  | 0.4321 | 0.1118 |
| 0.4994        | 5.0   | 7745  | inf             | 0.005                  | 0.4350 | 0.1131 |
| 0.4831        | 6.0   | 9294  | inf             | 0.005                  | 0.4462 | 0.1256 |
| 0.4959        | 7.0   | 10843 | inf             | 0.005                  | 0.7363 | 0.1926 |
| 2.8986        | 8.0   | 12392 | nan             | 0.005                  | 0.7915 | 0.2142 |
| 0.0205        | 9.0   | 13941 | nan             | 0.005                  | 0.7915 | 0.2142 |
| 0.3227        | 10.0  | 15490 | nan             | 0.005                  | 0.7915 | 0.2142 |
| 0.4651        | 11.0  | 17039 | nan             | 0.005                  | 0.7915 | 0.2142 |
| 0.0061        | 12.0  | 18588 | nan             | 0.005                  | 0.7915 | 0.2142 |
| 0.1837        | 13.0  | 20137 | nan             | 0.005                  | 0.7915 | 0.2142 |
| 0.0034        | 14.0  | 21686 | nan             | 0.005                  | 0.7915 | 0.2142 |
| 0.0246        | 15.0  | 23235 | nan             | 0.005                  | 0.7915 | 0.2142 |
| 0.0123        | 16.0  | 24784 | nan             | 0.005                  | 0.7915 | 0.2142 |
| 0.009         | 17.0  | 26333 | nan             | 0.005                  | 0.7915 | 0.2142 |
| 0.0321        | 18.0  | 27882 | nan             | 0.005                  | 1.0    | 1.0    |
| 0.0           | 19.0  | 29431 | nan             | 0.005                  | 1.0    | 1.0    |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.2.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1