metadata
language:
- sat
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- sat
- robust-speech-event
- model_for_talk
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-sat-final
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8
type: mozilla-foundation/common_voice_8_0
args: sat
metrics:
- name: Test WER
type: wer
value: 0.3493975903614458
- name: Test CER
type: cer
value: 0.13773314203730272
wav2vec2-large-xls-r-300m-sat-final
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.8012
- Wer: 0.3815
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: 0.0004
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 170
- num_epochs: 200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 10.6317 | 33.29 | 100 | 2.8629 | 1.0 |
| 2.047 | 66.57 | 200 | 0.9516 | 0.5703 |
| 0.4475 | 99.86 | 300 | 0.8539 | 0.3896 |
| 0.0716 | 133.29 | 400 | 0.8277 | 0.3454 |
| 0.047 | 166.57 | 500 | 0.7597 | 0.3655 |
| 0.0249 | 199.86 | 600 | 0.8012 | 0.3815 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0