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---
language:
- mn
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- mn
- model_for_talk
- mozilla-foundation/common_voice_7_0
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: XLS-R-300M - Mongolian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: mn
metrics:
- name: Test WER
type: wer
value: 44.709
- name: Test CER
type: cer
value: 13.532
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: mn
metrics:
- name: Test WER
type: wer
value: 76.643
- name: Test CER
type: cer
value: 36.997
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Test Data
type: speech-recognition-community-v2/eval_data
args: mn
metrics:
- name: Test WER
type: wer
value: 78.45
---
<!-- 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-xls-r-300m-mongolian
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_7_0 - MN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6003
- Wer: 0.4473
## 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: 32
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 100.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.3677 | 15.87 | 2000 | 0.6432 | 0.6198 |
| 1.1379 | 31.75 | 4000 | 0.6196 | 0.5592 |
| 1.0093 | 47.62 | 6000 | 0.5828 | 0.5117 |
| 0.8888 | 63.49 | 8000 | 0.5754 | 0.4822 |
| 0.7985 | 79.37 | 10000 | 0.5987 | 0.4690 |
| 0.697 | 95.24 | 12000 | 0.6014 | 0.4471 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0
|