| --- |
| 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 |
| - hf-asr-leaderboard |
| datasets: |
| - mozilla-foundation/common_voice_8_0 |
| model-index: |
| - name: wav2vec2-large-xls-r-300m-sat-a3 |
| 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: 0.357429718875502 |
| - name: Test CER |
| type: cer |
| value: 0.14203730272596843 |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Robust Speech Event - Dev Data |
| type: speech-recognition-community-v2/dev_data |
| args: sat |
| metrics: |
| - name: Test WER |
| type: wer |
| value: NA |
| - name: Test CER |
| type: cer |
| value: NA |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # wav2vec2-large-xls-r-300m-sat-a3 |
|
|
| 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_8_0 - SAT dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8961 |
| - Wer: 0.3976 |
| |
| ### Evaluation Commands |
| |
| 1. To evaluate on mozilla-foundation/common_voice_8_0 with test split |
|
|
| python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-sat-a3 --dataset mozilla-foundation/common_voice_8_0 --config sat --split test --log_outputs |
| |
| 2. To evaluate on speech-recognition-community-v2/dev_data |
|
|
| Note: Santali (Ol Chiki) language not found in speech-recognition-community-v2/dev_data |
| |
| |
| ### 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: 200 |
| - num_epochs: 200 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:------:|:----:|:---------------:|:------:| |
| | 11.1266 | 33.29 | 100 | 2.8577 | 1.0 | |
| | 2.1549 | 66.57 | 200 | 1.0799 | 0.5542 | |
| | 0.5628 | 99.86 | 300 | 0.7973 | 0.4016 | |
| | 0.0779 | 133.29 | 400 | 0.8424 | 0.4177 | |
| | 0.0404 | 166.57 | 500 | 0.9048 | 0.4137 | |
| | 0.0212 | 199.86 | 600 | 0.8961 | 0.3976 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.16.2 |
| - Pytorch 1.10.0+cu111 |
| - Datasets 1.18.3 |
| - Tokenizers 0.11.0 |
| |
