--- language: - gl license: apache-2.0 tags: - automatic-speech-recognition - mozilla-foundation/common_voice_8_0 - generated_from_trainer - gl - robust-speech-event - model_for_talk datasets: - mozilla-foundation/common_voice_8_0 model-index: - name: Akashpb13/Galician_xlsr results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 8 type: mozilla-foundation/common_voice_8_0 args: kmr metrics: - name: Test WER type: wer value: 0.11308483789555426 - name: Test CER type: cer value: 0.023982371794871796 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Robust Speech Event - Dev Data type: speech-recognition-community-v2/dev_data args: gl metrics: - name: Test WER type: wer value: 0.11308483789555426 - name: Test CER type: cer value: 0.023982371794871796 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 8.0 type: mozilla-foundation/common_voice_8_0 args: gl metrics: - name: Test WER type: wer value: 11.31 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Robust Speech Event - Test Data type: speech-recognition-community-v2/eval_data args: gl metrics: - name: Test WER type: wer value: 39.05 --- # Akashpb13/Galician_xlsr This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - hu dataset. It achieves the following results on the evaluation set (which is 10 percent of train data set merged with invalidated data, reported, other, and dev datasets): - Loss: 0.137096 - Wer: 0.196230 ## Model description "facebook/wav2vec2-xls-r-300m" was finetuned. ## Intended uses & limitations More information needed ## Training and evaluation data Training data - Common voice Galician train.tsv, dev.tsv, invalidated.tsv, reported.tsv, and other.tsv Only those points were considered where upvotes were greater than downvotes and duplicates were removed after concatenation of all the datasets given in common voice 7.0 ## Training procedure For creating the training dataset, all possible datasets were appended and 90-10 split was used. ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.000096 - train_batch_size: 16 - eval_batch_size: 16 - seed: 13 - gradient_accumulation_steps: 2 - lr_scheduler_type: cosine_with_restarts - lr_scheduler_warmup_steps: 500 - num_epochs: 100 - mixed_precision_training: Native AMP ### Training results | Step | Training Loss | Validation Loss | Wer | |------|---------------|-----------------|----------| | 500 | 5.038100 | 3.035432 | 1.000000 | | 1000 | 2.180000 | 0.406300 | 0.557964 | | 1500 | 0.331700 | 0.153797 | 0.262394 | | 2000 | 0.171600 | 0.145268 | 0.235627 | | 2500 | 0.125900 | 0.136622 | 0.228087 | | 3000 | 0.105400 | 0.131650 | 0.224128 | | 3500 | 0.087600 | 0.141032 | 0.217531 | | 4000 | 0.078300 | 0.143675 | 0.214515 | | 4500 | 0.070000 | 0.144607 | 0.208106 | | 5000 | 0.061500 | 0.135259 | 0.202828 | | 5500 | 0.055600 | 0.130638 | 0.203959 | | 6000 | 0.050500 | 0.137416 | 0.202451 | | 6500 | 0.046600 | 0.140379 | 0.200000 | | 7000 | 0.040800 | 0.140179 | 0.200377 | | 7500 | 0.041000 | 0.138089 | 0.196795 | | 8000 | 0.038400 | 0.136927 | 0.197172 | ### Framework versions - Transformers 4.16.0.dev0 - Pytorch 1.10.0+cu102 - Datasets 1.18.3 - Tokenizers 0.10.3 #### Evaluation Commands 1. To evaluate on `mozilla-foundation/common_voice_8_0` with split `test` ```bash python eval.py --model_id Akashpb13/Galician_xlsr --dataset mozilla-foundation/common_voice_8_0 --config gl --split test ```