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---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice_7_0
metrics:
- wer
model-index:
- name: luganda_wav2vec2_ctc_train_clean
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: 0.4156354350815164
---
<!-- 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_train_clean
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_7_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2835
- Wer: 0.4156
## 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: 32
- 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: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.8861 | 2.4 | 500 | 3.1284 | 1.0 |
| 2.0448 | 4.81 | 1000 | 0.5439 | 0.7131 |
| 0.6342 | 7.21 | 1500 | 0.3713 | 0.5556 |
| 0.4907 | 9.62 | 2000 | 0.3464 | 0.5015 |
| 0.4242 | 12.02 | 2500 | 0.3122 | 0.4746 |
| 0.3898 | 14.42 | 3000 | 0.3164 | 0.4634 |
| 0.357 | 16.83 | 3500 | 0.2896 | 0.4416 |
| 0.3338 | 19.23 | 4000 | 0.2880 | 0.4409 |
| 0.3223 | 21.63 | 4500 | 0.2841 | 0.4287 |
| 0.3072 | 24.04 | 5000 | 0.2849 | 0.4250 |
| 0.2974 | 26.44 | 5500 | 0.2829 | 0.4194 |
| 0.2878 | 28.85 | 6000 | 0.2835 | 0.4156 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.2.1+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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