| --- |
| language: |
| - en |
| license: mit |
| base_model: distil-whisper/distil-small.en |
| tags: |
| - generated_from_trainer |
| datasets: |
| - atc |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Large v3 1500 Epochs 2 - nullonesix |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: atc |
| type: atc |
| args: 'config: en, split: test' |
| metrics: |
| - name: Wer |
| type: wer |
| value: 39.23487544483986 |
| --- |
| |
| <!-- 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 1500 Epochs 2 - nullonesix |
|
|
| This model is a fine-tuned version of [distil-whisper/distil-small.en](https://huggingface.co/distil-whisper/distil-small.en) on the atc dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.4151 |
| - Wer: 39.2349 |
|
|
| ## 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: 1e-05 |
| - 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: 500 |
| - training_steps: 1500 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-------:|:----:|:---------------:|:-------:| |
| | 2.8313 | 3.5714 | 100 | 2.7177 | 74.1548 | |
| | 1.1366 | 7.1429 | 200 | 1.6407 | 63.0338 | |
| | 0.4394 | 10.7143 | 300 | 1.4737 | 47.4644 | |
| | 0.1686 | 14.2857 | 400 | 1.4481 | 46.3968 | |
| | 0.0761 | 17.8571 | 500 | 1.3707 | 40.8808 | |
| | 0.0452 | 21.4286 | 600 | 1.4051 | 38.5231 | |
| | 0.0188 | 25.0 | 700 | 1.4044 | 36.7883 | |
| | 0.0167 | 28.5714 | 800 | 1.4217 | 38.8345 | |
| | 0.0084 | 32.1429 | 900 | 1.4120 | 48.5765 | |
| | 0.0033 | 35.7143 | 1000 | 1.4151 | 39.2349 | |
| | 0.0022 | 39.2857 | 1100 | 1.4401 | 39.7242 | |
| | 0.0008 | 42.8571 | 1200 | 1.4591 | 39.5907 | |
| | 0.0007 | 46.4286 | 1300 | 1.4679 | 39.5907 | |
| | 0.0006 | 50.0 | 1400 | 1.4724 | 39.8577 | |
| | 0.0007 | 53.5714 | 1500 | 1.4737 | 39.7242 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.42.3 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
| |
