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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-common_voice_13_0-eo-10
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: eo
split: validation
args: eo
metrics:
- name: Wer
type: wer
value: 0.06575168361283507
---
<!-- 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-common_voice_13_0-eo-10
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:
- Cer: 0.0119
- Loss: 0.0454
- Wer: 0.0658
## 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: 3e-05
- 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: 500
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Cer | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:------:|:---------------:|:------:|
| 2.9894 | 0.22 | 1000 | 1.0 | 2.9257 | 1.0 |
| 0.7104 | 0.44 | 2000 | 0.0457 | 0.2129 | 0.2538 |
| 0.2853 | 0.67 | 3000 | 0.0274 | 0.1109 | 0.1583 |
| 0.2327 | 0.89 | 4000 | 0.0231 | 0.0909 | 0.1320 |
| 0.1917 | 1.11 | 5000 | 0.0206 | 0.0775 | 0.1188 |
| 0.1803 | 1.33 | 6000 | 0.0184 | 0.0698 | 0.1055 |
| 0.1661 | 1.56 | 7000 | 0.0169 | 0.0645 | 0.0961 |
| 0.1635 | 1.78 | 8000 | 0.0170 | 0.0639 | 0.0964 |
| 0.1555 | 2.0 | 9000 | 0.0156 | 0.0592 | 0.0881 |
| 0.1386 | 2.22 | 10000 | 0.0147 | 0.0559 | 0.0821 |
| 0.1338 | 2.45 | 11000 | 0.0146 | 0.0548 | 0.0831 |
| 0.1307 | 2.67 | 12000 | 0.0137 | 0.0529 | 0.0759 |
| 0.1297 | 2.89 | 13000 | 0.0134 | 0.0504 | 0.0745 |
| 0.1201 | 3.11 | 14000 | 0.0131 | 0.0499 | 0.0734 |
| 0.1152 | 3.34 | 15000 | 0.0128 | 0.0484 | 0.0712 |
| 0.1144 | 3.56 | 16000 | 0.0125 | 0.0477 | 0.0695 |
| 0.1179 | 3.78 | 17000 | 0.0122 | 0.0468 | 0.0679 |
| 0.1112 | 4.0 | 18000 | 0.0121 | 0.0468 | 0.0676 |
| 0.1141 | 4.23 | 19000 | 0.0121 | 0.0462 | 0.0668 |
| 0.1085 | 4.45 | 20000 | 0.0119 | 0.0458 | 0.0664 |
| 0.105 | 4.67 | 21000 | 0.0119 | 0.0456 | 0.0660 |
| 0.1072 | 4.89 | 22000 | 0.0119 | 0.0454 | 0.0658 |
### Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
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