metadata
language:
- ky
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
- ky
- robust-speech-event
- model_for_talk
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: XLS-R-300M - Kyrgyz
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: ky
metrics:
- name: Test WER
type: wer
value: 40.908
- name: Test CER
type: cer
value: 10.999
wav2vec2-large-xls-r-300m-kyrgyz
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - KY dataset. It achieves the following results on the evaluation set:
- Loss: 0.5817
- Wer: 0.4096
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 |
|---|---|---|---|---|
| 1.5412 | 18.69 | 2000 | 0.6161 | 0.5747 |
| 1.311 | 37.38 | 4000 | 0.5707 | 0.5070 |
| 1.1367 | 56.07 | 6000 | 0.5372 | 0.4664 |
| 0.9696 | 74.77 | 8000 | 0.5443 | 0.4328 |
| 0.8163 | 93.46 | 10000 | 0.5916 | 0.4124 |
Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0