metadata
license: mit
base_model: distil-whisper/distil-large-v3
tags:
- generated_from_trainer
datasets:
- ravnursson_asr
metrics:
- wer
model-index:
- name: distil-whisper-large-fo-100h-5k-steps
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: ravnursson_asr
type: ravnursson_asr
config: ravnursson_asr
split: test
args: ravnursson_asr
metrics:
- name: Wer
type: wer
value: 13.55445943225287
distil-whisper-large-fo-100h-5k-steps
This model is a fine-tuned version of distil-whisper/distil-large-v3 on the ravnursson_asr dataset. It achieves the following results on the evaluation set:
- Loss: 0.2075
- Wer: 13.5545
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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4469 | 0.2320 | 1000 | 0.5128 | 30.3201 |
| 0.2995 | 0.4640 | 2000 | 0.3383 | 21.1295 |
| 0.2338 | 0.6961 | 3000 | 0.2666 | 17.4351 |
| 0.2009 | 0.9281 | 4000 | 0.2270 | 14.9940 |
| 0.0963 | 1.1601 | 5000 | 0.2075 | 13.5545 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1