| --- |
| language: |
| - pa-IN |
| license: apache-2.0 |
| tags: |
| - automatic-speech-recognition |
| - mozilla-foundation/common_voice_8_0 |
| - generated_from_trainer |
| - pa-IN |
| - robust-speech-event |
| - hf-asr-leaderboard |
| datasets: |
| - mozilla-foundation/common_voice_8_0 |
| model-index: |
| - name: wav2vec2-large-xls-r-300m-pa-IN-dx1 |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Common Voice 8 |
| type: mozilla-foundation/common_voice_8_0 |
| args: pa-IN |
| metrics: |
| - name: Test WER |
| type: wer |
| value: 0.48725989807918463 |
| - name: Test CER |
| type: cer |
| value: 0.1687305197540224 |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Robust Speech Event - Dev Data |
| type: speech-recognition-community-v2/dev_data |
| args: pa-IN |
| 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. --> |
|
|
| # |
|
|
| 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 - PA-IN dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.0855 |
| - Wer: 0.4755 |
| |
| |
| ### 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-pa-IN-dx1 --dataset mozilla-foundation/common_voice_8_0 --config pa-IN --split test --log_outputs |
| |
| 2. To evaluate on speech-recognition-community-v2/dev_data |
|
|
| Punjabi language isn't available in speech-recognition-community-v2/dev_data |
| |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 0.0003 |
| - train_batch_size: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 1200 |
| - num_epochs: 100.0 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | 3.4607 | 9.26 | 500 | 2.7746 | 1.0416 | |
| | 0.3442 | 18.52 | 1000 | 0.9114 | 0.5911 | |
| | 0.2213 | 27.78 | 1500 | 0.9687 | 0.5751 | |
| | 0.1242 | 37.04 | 2000 | 1.0204 | 0.5461 | |
| | 0.0998 | 46.3 | 2500 | 1.0250 | 0.5233 | |
| | 0.0727 | 55.56 | 3000 | 1.1072 | 0.5382 | |
| | 0.0605 | 64.81 | 3500 | 1.0588 | 0.5073 | |
| | 0.0458 | 74.07 | 4000 | 1.0818 | 0.5069 | |
| | 0.0338 | 83.33 | 4500 | 1.0948 | 0.5108 | |
| | 0.0223 | 92.59 | 5000 | 1.0986 | 0.4775 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.17.0.dev0 |
| - Pytorch 1.10.2+cu102 |
| - Datasets 1.18.2.dev0 |
| - Tokenizers 0.11.0 |
|
|
