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---
language:
- sah
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
- sah
- robust-speech-event
- model_for_talk
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: XLS-R-300M - Sakha
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: sah
metrics:
- name: Test WER
type: wer
value: 44.196
- name: Test CER
type: cer
value: 10.271
---
<!-- 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-sakha
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 - SAH dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4995
- Wer: 0.4421
## 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: 500
- num_epochs: 100.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.8597 | 8.47 | 500 | 0.7731 | 0.7211 |
| 1.2508 | 16.95 | 1000 | 0.5368 | 0.5989 |
| 1.1066 | 25.42 | 1500 | 0.5034 | 0.5533 |
| 1.0064 | 33.9 | 2000 | 0.4686 | 0.5114 |
| 0.9324 | 42.37 | 2500 | 0.4927 | 0.5056 |
| 0.876 | 50.85 | 3000 | 0.4734 | 0.4795 |
| 0.8082 | 59.32 | 3500 | 0.4748 | 0.4799 |
| 0.7604 | 67.8 | 4000 | 0.4949 | 0.4691 |
| 0.7241 | 76.27 | 4500 | 0.5090 | 0.4627 |
| 0.6739 | 84.75 | 5000 | 0.4967 | 0.4452 |
| 0.6447 | 93.22 | 5500 | 0.5071 | 0.4437 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0
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