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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-AsanteTwi-05
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: tw
split: test
args: tw
metrics:
- name: Wer
type: wer
value: 0.75
---
<!-- 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-large-xlsr-53-AsanteTwi-05
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_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7657
- Wer: 0.75
## 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: 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: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 150
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 2.2241 | 16.67 | 100 | 2.1317 | 1.0 |
| 1.5168 | 33.33 | 200 | 1.1019 | 0.8125 |
| 0.7964 | 50.0 | 300 | 0.7658 | 0.75 |
| 0.4985 | 66.67 | 400 | 0.6807 | 0.625 |
| 0.3885 | 83.33 | 500 | 0.7197 | 0.5625 |
| 0.3269 | 100.0 | 600 | 0.7616 | 0.5625 |
| 0.2625 | 116.67 | 700 | 0.7000 | 0.6875 |
| 0.2595 | 133.33 | 800 | 0.7425 | 0.6875 |
| 0.2388 | 150.0 | 900 | 0.7657 | 0.75 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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