|
--- |
|
library_name: transformers |
|
language: |
|
- en |
|
license: apache-2.0 |
|
base_model: openai/whisper-large-v3 |
|
tags: |
|
- wft |
|
- whisper |
|
- automatic-speech-recognition |
|
- audio |
|
- speech |
|
- generated_from_trainer |
|
datasets: |
|
- ntnu-smil/ami-1s-ft |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: whisper-large-v3-ami-1 |
|
results: |
|
- task: |
|
type: automatic-speech-recognition |
|
name: Automatic Speech Recognition |
|
dataset: |
|
name: ntnu-smil/ami-1s-ft |
|
type: ntnu-smil/ami-1s-ft |
|
metrics: |
|
- type: wer |
|
value: 73.28296703296702 |
|
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-ami-1 |
|
|
|
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the ntnu-smil/ami-1s-ft dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 3.6457 |
|
- Wer: 73.2830 |
|
- Cer: 65.1890 |
|
- Decode Runtime: 3.7197 |
|
- Wer Runtime: 0.0090 |
|
- Cer Runtime: 0.0152 |
|
|
|
## 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: 128 |
|
- eval_batch_size: 128 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 1024 |
|
- optimizer: Use adamw_torch with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 50 |
|
- training_steps: 130 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Decode Runtime | Wer Runtime | Cer Runtime | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:--------------:|:-----------:|:-----------:| |
|
| 2.2365 | 0.0769 | 10 | 3.2101 | 71.2225 | 305.1720 | 5.7416 | 0.0099 | 0.0322 | |
|
| 1.9464 | 0.1538 | 20 | 3.1678 | 81.2843 | 319.6875 | 5.8313 | 0.0098 | 0.0337 | |
|
| 1.5994 | 0.2308 | 30 | 3.0765 | 106.4904 | 341.3692 | 5.8220 | 0.0105 | 0.0351 | |
|
| 1.1357 | 0.3077 | 40 | 3.2982 | 129.5330 | 214.6070 | 5.6144 | 0.0102 | 0.0259 | |
|
| 0.4404 | 0.3846 | 50 | 3.4638 | 72.2871 | 98.6465 | 3.8830 | 0.0093 | 0.0179 | |
|
| 0.3252 | 0.4615 | 60 | 3.3927 | 65.1099 | 80.9729 | 3.7645 | 0.0091 | 0.0167 | |
|
| 0.3713 | 1.0231 | 70 | 3.4800 | 58.9629 | 49.3854 | 3.4950 | 0.0090 | 0.0142 | |
|
| 0.2562 | 1.1 | 80 | 3.5965 | 54.0522 | 31.3522 | 3.3013 | 0.0089 | 0.0130 | |
|
| 0.1821 | 1.1769 | 90 | 3.6241 | 70.4327 | 56.6693 | 3.6241 | 0.0089 | 0.0146 | |
|
| 0.1847 | 1.2538 | 100 | 3.6725 | 66.2775 | 50.4512 | 3.6175 | 0.0090 | 0.2387 | |
|
| 0.2257 | 1.3308 | 110 | 3.6518 | 64.8695 | 50.6408 | 3.5330 | 0.0090 | 0.0141 | |
|
| 0.2672 | 1.4077 | 120 | 3.6463 | 69.7802 | 59.8928 | 3.6917 | 0.0090 | 0.0146 | |
|
| 0.2578 | 1.4846 | 130 | 3.6457 | 73.2830 | 65.1890 | 3.7197 | 0.0090 | 0.0152 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.14.0 |
|
- Transformers 4.48.0 |
|
- Pytorch 2.5.1 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.21.0 |
