metadata
language:
- ha
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- robust-speech-event
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: ''
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8.0
type: mozilla-foundation/common_voice_8_0
args: ha
metrics:
- name: Test WER
type: wer
value: 51.31
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - HA dataset. It achieves the following results on the evaluation set:
- Loss: 0.4998
- Wer: 0.5153
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: 9.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 2000
- num_epochs: 80.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.0021 | 8.33 | 500 | 2.9059 | 1.0 |
| 2.6604 | 16.66 | 1000 | 2.6402 | 0.9892 |
| 1.2216 | 24.99 | 1500 | 0.6051 | 0.6851 |
| 1.0754 | 33.33 | 2000 | 0.5408 | 0.6464 |
| 0.9582 | 41.66 | 2500 | 0.5521 | 0.5935 |
| 0.8653 | 49.99 | 3000 | 0.5156 | 0.5550 |
| 0.7867 | 58.33 | 3500 | 0.5439 | 0.5606 |
| 0.7265 | 66.66 | 4000 | 0.4863 | 0.5255 |
| 0.6699 | 74.99 | 4500 | 0.5050 | 0.5169 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu113
- Datasets 1.18.4.dev0
- Tokenizers 0.11.0