metadata
language:
- ro
license: apache-2.0
tags:
- automatic-speech-recognition
- generated_from_trainer
- hf-asr-leaderboard
- model_for_talk
- mozilla-foundation/common_voice_7_0
- ro
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: XLS-R-300M - Romanian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7
type: mozilla-foundation/common_voice_7_0
args: ro
metrics:
- name: Test WER
type: wer
value: 14.194
- name: Test CER
type: cer
value: 3.288
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: ro
metrics:
- name: Test WER
type: wer
value: 40.869
- name: Test CER
type: cer
value: 12.049
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Test Data
type: speech-recognition-community-v2/eval_data
args: ro
metrics:
- name: Test WER
type: wer
value: 47.2
wav2vec2-large-xls-r-300m-romanian
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - RO dataset. It achieves the following results on the evaluation set:
- Loss: 0.1167
- Wer: 0.1421
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: 7e-05
- 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: 50.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
1.1973 | 8.89 | 2000 | 0.4481 | 0.4849 |
0.6005 | 17.78 | 4000 | 0.1420 | 0.1777 |
0.5248 | 26.67 | 6000 | 0.1303 | 0.1651 |
0.4871 | 35.56 | 8000 | 0.1207 | 0.1523 |
0.4428 | 44.44 | 10000 | 0.1143 | 0.1425 |
Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0