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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- common_voice_7_0
metrics:
- wer
model-index:
- name: luganda_wav2vec2_ctc
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_7_0
type: common_voice_7_0
config: lg
split: None
args: lg
metrics:
- name: Wer
type: wer
value: 0.5421986512145617
---
<!-- 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. -->
# luganda_wav2vec2_ctc
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the common_voice_7_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7622
- Wer: 0.5422
## 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: 48
- 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: 60
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.2675 | 3.6 | 500 | 1.9999 | 0.9999 |
| 0.5754 | 7.19 | 1000 | 0.6976 | 0.7050 |
| 0.231 | 10.79 | 1500 | 0.6153 | 0.6440 |
| 0.1557 | 14.39 | 2000 | 0.6581 | 0.6130 |
| 0.1221 | 17.99 | 2500 | 0.6718 | 0.6063 |
| 0.1013 | 21.58 | 3000 | 0.6711 | 0.5934 |
| 0.0871 | 25.18 | 3500 | 0.6728 | 0.5731 |
| 0.0751 | 28.78 | 4000 | 0.6729 | 0.5726 |
| 0.0666 | 32.37 | 4500 | 0.6884 | 0.5689 |
| 0.0604 | 35.97 | 5000 | 0.7452 | 0.5609 |
| 0.0543 | 39.57 | 5500 | 0.7302 | 0.5616 |
| 0.0488 | 43.17 | 6000 | 0.7414 | 0.5480 |
| 0.0448 | 46.76 | 6500 | 0.7662 | 0.5560 |
| 0.042 | 50.36 | 7000 | 0.7629 | 0.5433 |
| 0.038 | 53.96 | 7500 | 0.7582 | 0.5479 |
| 0.0353 | 57.55 | 8000 | 0.7622 | 0.5422 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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