|
|
| --- |
| language: |
| - ka |
| license: apache-2.0 |
| tags: |
| - automatic-speech-recognition |
| - mozilla-foundation/common_voice_8_0 |
| - generated_from_trainer |
| - robust-speech-event |
| - hf-asr-leaderboard |
| datasets: |
| - common_voice |
| model-index: |
| - name: wav2vec2-xls-r-1b-ka |
| results: |
| - task: |
| type: automatic-speech-recognition |
| name: Speech Recognition |
| dataset: |
| type: mozilla-foundation/common_voice_8_0 |
| name: Common Voice ka |
| args: ka |
| metrics: |
| - type: wer |
| value: 7.39778066580026 |
| name: WER LM |
| - type: cer |
| value: 1.1882089427096434 |
| name: CER LM |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Robust Speech Event - Dev Data |
| type: speech-recognition-community-v2/dev_data |
| args: ka |
| metrics: |
| - name: Test WER |
| type: wer |
| value: 22.61 |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Robust Speech Event - Test Data |
| type: speech-recognition-community-v2/eval_data |
| args: ka |
| metrics: |
| - name: Test WER |
| type: wer |
| value: 21.58 |
| --- |
| |
| <!-- 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-xls-r-1b-ka |
|
|
| This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the /WORKSPACE/DATA/KA/NOIZY_STUDENT_2/ - KA dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1022 |
| - Wer: 0.1527 |
| - Cer: 0.0221 |
|
|
| ## 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: 16 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 128 |
| - optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.1 |
| - training_steps: 4000 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
| | 1.2839 | 6.45 | 400 | 0.2229 | 0.3609 | 0.0557 | |
| | 0.9775 | 12.9 | 800 | 0.1271 | 0.2202 | 0.0317 | |
| | 0.9045 | 19.35 | 1200 | 0.1268 | 0.2030 | 0.0294 | |
| | 0.8652 | 25.8 | 1600 | 0.1211 | 0.1940 | 0.0287 | |
| | 0.8505 | 32.26 | 2000 | 0.1192 | 0.1912 | 0.0276 | |
| | 0.8168 | 38.7 | 2400 | 0.1086 | 0.1763 | 0.0260 | |
| | 0.7737 | 45.16 | 2800 | 0.1098 | 0.1753 | 0.0256 | |
| | 0.744 | 51.61 | 3200 | 0.1054 | 0.1646 | 0.0239 | |
| | 0.7114 | 58.06 | 3600 | 0.1034 | 0.1573 | 0.0228 | |
| | 0.6773 | 64.51 | 4000 | 0.1022 | 0.1527 | 0.0221 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.17.0.dev0 |
| - Pytorch 1.10.2 |
| - Datasets 1.18.4.dev0 |
| - Tokenizers 0.11.0 |
|
|
