---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: swahili_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. -->

# swahili_v2

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5957
- Wer: 0.4820

## 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: 3
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.0806        | 0.6   | 1000  | 1.2990          | 0.9279 |
| 1.3262        | 1.2   | 2000  | 0.9359          | 0.8004 |
| 1.0778        | 1.8   | 3000  | 1.0139          | 0.7421 |
| 0.9227        | 2.4   | 4000  | 0.7815          | 0.7053 |
| 0.8283        | 3.0   | 5000  | 0.6969          | 0.6340 |
| 0.683         | 3.6   | 6000  | 0.6665          | 0.6254 |
| 0.6208        | 4.2   | 7000  | 0.6304          | 0.5900 |
| 0.561         | 4.8   | 8000  | 0.5912          | 0.5748 |
| 0.4881        | 5.4   | 9000  | 0.5998          | 0.5523 |
| 0.474         | 6.0   | 10000 | 0.5488          | 0.5409 |
| 0.3989        | 6.6   | 11000 | 0.5550          | 0.5274 |
| 0.3581        | 7.2   | 12000 | 0.5702          | 0.5088 |
| 0.3348        | 7.8   | 13000 | 0.5739          | 0.5034 |
| 0.3059        | 8.4   | 14000 | 0.5915          | 0.5042 |
| 0.2765        | 9.0   | 15000 | 0.5720          | 0.4860 |
| 0.2489        | 9.6   | 16000 | 0.5957          | 0.4820 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3