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---
language:
- mr
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- mozilla-foundation/common_voice_8_0
- mr
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: ''
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice Corpus 8.0
type: mozilla-foundation/common_voice_8_0
args: mr
metrics:
- name: Test WER
type: wer
value: 38.27
- name: Test CER
type: cer
value: 8.91
---
<!-- 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-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - MR dataset.
It achieves the following results on the mozilla-foundation/common_voice_8_0 mr test set:
- Without LM
+ WER: 48.53
+ CER: 10.63
- With LM
+ WER: 38.27
+ CER: 8.91
## 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: 4
- 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: 2000
- num_epochs: 400.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 4.2706 | 22.73 | 500 | 4.0174 | 1.0 |
| 3.2492 | 45.45 | 1000 | 3.2309 | 0.9908 |
| 1.9709 | 68.18 | 1500 | 1.0651 | 0.8440 |
| 1.4088 | 90.91 | 2000 | 0.5765 | 0.6550 |
| 1.1326 | 113.64 | 2500 | 0.4842 | 0.5760 |
| 0.9709 | 136.36 | 3000 | 0.4785 | 0.6013 |
| 0.8433 | 159.09 | 3500 | 0.5048 | 0.5419 |
| 0.7404 | 181.82 | 4000 | 0.5052 | 0.5339 |
| 0.6589 | 204.55 | 4500 | 0.5237 | 0.5897 |
| 0.5831 | 227.27 | 5000 | 0.5166 | 0.5447 |
| 0.5375 | 250.0 | 5500 | 0.5292 | 0.5487 |
| 0.4784 | 272.73 | 6000 | 0.5480 | 0.5596 |
| 0.4421 | 295.45 | 6500 | 0.5682 | 0.5467 |
| 0.4047 | 318.18 | 7000 | 0.5681 | 0.5447 |
| 0.3779 | 340.91 | 7500 | 0.5783 | 0.5347 |
| 0.3525 | 363.64 | 8000 | 0.5856 | 0.5367 |
| 0.3393 | 386.36 | 8500 | 0.5960 | 0.5359 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu113
- Datasets 1.18.1.dev0
- Tokenizers 0.11.0
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