metadata
language:
- rm-vallader
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- rm-vallader
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: XLS-R-300M - Tatar
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_8_0
args: rm-vallader
metrics:
- name: Test WER
type: wer
value: 0.26472007722007723
- name: Test CER
type: cer
value: 0.05860608074430969
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - RM-VALLADER dataset. It achieves the following results on the evaluation set:
- Loss: 0.2754
- Wer: 0.2831
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: 32
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|
| 2.927 | 15.15 | 500 | 2.9196 | 1.0 |
| 1.3835 | 30.3 | 1000 | 0.5879 | 0.5866 |
| 0.7415 | 45.45 | 1500 | 0.3077 | 0.3316 |
| 0.5575 | 60.61 | 2000 | 0.2735 | 0.2954 |
| 0.4581 | 75.76 | 2500 | 0.2707 | 0.2802 |
| 0.3977 | 90.91 | 3000 | 0.2785 | 0.2809 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0