| --- |
| library_name: peft |
| language: |
| - en |
| license: apache-2.0 |
| base_model: openai/whisper-large-v3 |
| tags: |
| - wft |
| - whisper |
| - automatic-speech-recognition |
| - audio |
| - speech |
| - generated_from_trainer |
| datasets: |
| - JacobLinCool/ami-disfluent |
| metrics: |
| - wer |
| model-index: |
| - name: whisper-large-v3-verbatim-1 |
| results: |
| - task: |
| type: automatic-speech-recognition |
| name: Automatic Speech Recognition |
| dataset: |
| name: JacobLinCool/ami-disfluent |
| type: JacobLinCool/ami-disfluent |
| metrics: |
| - type: wer |
| value: 32.322538548713894 |
| name: Wer |
| --- |
| |
| <!-- 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. --> |
|
|
| # whisper-large-v3-verbatim-1 |
|
|
| This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the JacobLinCool/ami-disfluent dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1300 |
| - Wer: 32.3225 |
| - Cer: 45.5147 |
| - Decode Runtime: 141.5643 |
| - Wer Runtime: 0.1227 |
| - Cer Runtime: 0.2049 |
|
|
| ## 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: 5e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - gradient_accumulation_steps: 16 |
| - total_train_batch_size: 64 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 100 |
| - training_steps: 1000 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Decode Runtime | Wer Runtime | Cer Runtime | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:|:--------:|:--------------:|:-----------:|:-----------:| |
| | No log | 0 | 0 | 1.8283 | 63.2783 | 251.8035 | 164.5307 | 0.1838 | 0.3386 | |
| | 0.2617 | 0.1 | 100 | 0.2189 | 49.6995 | 178.3721 | 161.1098 | 0.1397 | 0.4071 | |
| | 0.1291 | 0.2 | 200 | 0.1452 | 50.3383 | 95.5275 | 143.0863 | 0.1342 | 0.2932 | |
| | 0.1418 | 0.3 | 300 | 0.1387 | 29.9186 | 74.6491 | 150.1053 | 0.0780 | 0.1514 | |
| | 0.1273 | 1.088 | 400 | 0.1372 | 30.8218 | 91.1134 | 166.0178 | 0.1252 | 0.2728 | |
| | 0.1139 | 1.188 | 500 | 0.1335 | 29.9117 | 101.9003 | 144.2796 | 0.1318 | 0.2934 | |
| | 0.1663 | 1.288 | 600 | 0.1306 | 31.8418 | 83.0183 | 149.9060 | 0.0826 | 0.1679 | |
| | 0.1275 | 2.076 | 700 | 0.1311 | 24.9665 | 29.6191 | 143.2151 | 0.0781 | 0.1135 | |
| | 0.1077 | 2.176 | 800 | 0.1304 | 25.9109 | 36.6217 | 143.4620 | 0.0770 | 0.1227 | |
| | 0.1711 | 2.276 | 900 | 0.1298 | 35.1729 | 45.0300 | 145.3294 | 0.0786 | 0.1310 | |
| | 0.0994 | 3.064 | 1000 | 0.1300 | 32.3225 | 45.5147 | 141.5643 | 0.1227 | 0.2049 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.14.0 |
| - Transformers 4.48.0 |
| - Pytorch 2.4.1+cu124 |
| - Datasets 3.2.0 |
| - Tokenizers 0.21.0 |
