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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-ur
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: ur
split: test
args: ur
metrics:
- name: Wer
type: wer
value: 0.4816893775162589
---
<!-- 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-ur
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_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.4817
## 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: 0.0003
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 12
- total_eval_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.0981 | 0.48 | 300 | inf | 0.9981 |
| 2.0031 | 0.97 | 600 | inf | 0.8283 |
| 0.7476 | 1.45 | 900 | inf | 0.6584 |
| 0.8585 | 1.94 | 1200 | inf | 0.5823 |
| 0.4978 | 2.42 | 1500 | inf | 0.5564 |
| 0.5423 | 2.9 | 1800 | inf | 0.5209 |
| 0.3504 | 3.39 | 2100 | inf | 0.5396 |
| 0.3185 | 3.87 | 2400 | inf | 0.4865 |
| 0.3337 | 4.35 | 2700 | inf | 0.4733 |
| 0.4935 | 4.84 | 3000 | inf | 0.4721 |
| 0.4022 | 5.32 | 3300 | inf | 0.4692 |
| 0.3517 | 5.81 | 3600 | inf | 0.4585 |
| 0.1838 | 6.29 | 3900 | inf | 0.4567 |
| 0.2635 | 6.77 | 4200 | inf | 0.4459 |
| 0.1163 | 7.26 | 4500 | inf | 0.4495 |
| 0.1776 | 7.74 | 4800 | inf | 0.4657 |
| 0.262 | 8.23 | 5100 | inf | 0.4562 |
| 0.1853 | 8.71 | 5400 | inf | 0.4724 |
| 0.3173 | 9.19 | 5700 | inf | 0.4752 |
| 0.4985 | 9.68 | 6000 | inf | 0.4604 |
| 0.3707 | 10.16 | 6300 | inf | 0.4769 |
| 0.4214 | 10.65 | 6600 | inf | 0.5246 |
| 0.3443 | 11.13 | 6900 | inf | 0.5391 |
| 0.3302 | 11.61 | 7200 | inf | 0.5051 |
| 0.327 | 12.1 | 7500 | inf | 0.5389 |
| 0.2489 | 12.58 | 7800 | inf | 0.5355 |
| 0.2328 | 13.06 | 8100 | inf | 0.5111 |
| 0.2488 | 13.55 | 8400 | inf | 0.4794 |
| 0.3255 | 14.03 | 8700 | inf | 0.4959 |
| 0.3056 | 14.52 | 9000 | inf | 0.4895 |
| 0.1758 | 15.0 | 9300 | inf | 0.4817 |
### Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2