metadata
language:
- hy-AM
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_7_0
- generated_from_trainer
- robust-speech-event
- hf-asr-leaderboard
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: XLS-R-300M - Armenian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: hy-AM
metrics:
- name: Test WER
type: wer
value: 101.627
- name: Test CER
type: cer
value: 158.767
wav2vec2-large-xls-r-300m-armenian
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - HY-AM dataset. It achieves the following results on the evaluation set:
- Loss: 0.9669
- Wer: 0.6942
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: 32
- 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: 200.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.7294 | 27.78 | 500 | 0.8540 | 0.9944 |
| 0.8863 | 55.56 | 1000 | 0.7282 | 0.7312 |
| 0.5789 | 83.33 | 1500 | 0.8178 | 0.8102 |
| 0.3899 | 111.11 | 2000 | 0.8034 | 0.7701 |
| 0.2869 | 138.89 | 2500 | 0.9061 | 0.6999 |
| 0.1934 | 166.67 | 3000 | 0.9400 | 0.7105 |
| 0.1551 | 194.44 | 3500 | 0.9667 | 0.6955 |
Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0