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---
language:
- ur
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- ur
- robust-speech-event
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: ''
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8.0
type: mozilla-foundation/common_voice_8_0
args: ur
metrics:
- name: Test WER
type: wer
value: 62.47
---
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - UR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8888
- Wer: 0.6642
## 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: 7.5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 50.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 10.1224 | 1.96 | 100 | 3.5429 | 1.0 |
| 3.2411 | 3.92 | 200 | 3.1786 | 1.0 |
| 3.1283 | 5.88 | 300 | 3.0571 | 1.0 |
| 3.0044 | 7.84 | 400 | 2.9560 | 0.9996 |
| 2.9388 | 9.8 | 500 | 2.8977 | 1.0011 |
| 2.86 | 11.76 | 600 | 2.6944 | 0.9952 |
| 2.5538 | 13.73 | 700 | 2.0967 | 0.9435 |
| 2.1214 | 15.69 | 800 | 1.4816 | 0.8428 |
| 1.8136 | 17.65 | 900 | 1.2459 | 0.8048 |
| 1.6795 | 19.61 | 1000 | 1.1232 | 0.7649 |
| 1.5571 | 21.57 | 1100 | 1.0510 | 0.7432 |
| 1.4975 | 23.53 | 1200 | 1.0298 | 0.6963 |
| 1.4485 | 25.49 | 1300 | 0.9775 | 0.7074 |
| 1.3924 | 27.45 | 1400 | 0.9798 | 0.6956 |
| 1.3604 | 29.41 | 1500 | 0.9345 | 0.7092 |
| 1.3224 | 31.37 | 1600 | 0.9535 | 0.6830 |
| 1.2816 | 33.33 | 1700 | 0.9178 | 0.6679 |
| 1.2623 | 35.29 | 1800 | 0.9249 | 0.6679 |
| 1.2421 | 37.25 | 1900 | 0.9124 | 0.6734 |
| 1.2208 | 39.22 | 2000 | 0.8962 | 0.6664 |
| 1.2145 | 41.18 | 2100 | 0.8903 | 0.6734 |
| 1.1888 | 43.14 | 2200 | 0.8883 | 0.6708 |
| 1.1933 | 45.1 | 2300 | 0.8928 | 0.6723 |
| 1.1838 | 47.06 | 2400 | 0.8868 | 0.6679 |
| 1.1634 | 49.02 | 2500 | 0.8886 | 0.6657 |
### Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0
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