---
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_20hr_v5
  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_20hr_v5

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: 0.5637
- Model Preparation Time: 0.0067
- Wer: 0.4975
- Cer: 0.1239

## 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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:------:|:------:|
| 6.9607        | 1.0   | 154  | inf             | 0.0067                 | 1.0    | 1.0    |
| 2.4999        | 2.0   | 308  | inf             | 0.0067                 | 0.9981 | 0.2571 |
| 0.8598        | 3.0   | 462  | inf             | 0.0067                 | 0.6688 | 0.1653 |
| 0.6842        | 4.0   | 616  | inf             | 0.0067                 | 0.7770 | 0.1976 |
| 0.6052        | 5.0   | 770  | inf             | 0.0067                 | 0.5482 | 0.1443 |
| 0.557         | 6.0   | 924  | inf             | 0.0067                 | 0.5141 | 0.1334 |
| 0.5169        | 7.0   | 1078 | inf             | 0.0067                 | 0.6443 | 0.1941 |
| 0.4708        | 8.0   | 1232 | inf             | 0.0067                 | 0.5685 | 0.1573 |
| 0.4684        | 9.0   | 1386 | inf             | 0.0067                 | 0.5414 | 0.1489 |
| 0.5716        | 10.0  | 1540 | inf             | 0.0067                 | 0.6515 | 0.1929 |
| 1.1996        | 11.0  | 1694 | inf             | 0.0067                 | 0.9517 | 0.3363 |
| 1.4771        | 12.0  | 1848 | inf             | 0.0067                 | 0.9655 | 0.3621 |
| 1.3761        | 13.0  | 2002 | inf             | 0.0067                 | 0.8545 | 0.2684 |
| 1.6064        | 14.0  | 2156 | inf             | 0.0067                 | 1.0    | 0.3888 |
| 1.8647        | 15.0  | 2310 | inf             | 0.0067                 | 0.9999 | 0.5035 |
| 1.7455        | 16.0  | 2464 | inf             | 0.0067                 | 1.0    | 0.3958 |
| 1.6089        | 17.0  | 2618 | inf             | 0.0067                 | 1.0    | 0.3634 |
| 1.4697        | 18.0  | 2772 | inf             | 0.0067                 | 0.9999 | 0.3466 |
| 1.4016        | 19.0  | 2926 | inf             | 0.0067                 | 1.0    | 0.3309 |
| 1.3563        | 20.0  | 3080 | inf             | 0.0067                 | 1.0    | 0.3232 |
| 1.3217        | 21.0  | 3234 | inf             | 0.0067                 | 0.9999 | 0.3116 |


### Framework versions

- Transformers 4.43.4
- Pytorch 2.2.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1