metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- nyagen
metrics:
- wer
model-index:
- name: whisper-large-v3-nyagen-combined-42
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: nyagen
type: nyagen
metrics:
- name: Wer
type: wer
value: 0.41069316299976344
whisper-large-v3-nyagen-combined-42
This model is a fine-tuned version of openai/whisper-large-v3 on the nyagen dataset. It achieves the following results on the evaluation set:
- Loss: 0.3866
- Wer: 0.4107
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4325 | 0.4935 | 200 | 0.5920 | 0.3963 |
| 0.2825 | 0.9870 | 400 | 0.4630 | 0.3549 |
| 0.2047 | 1.4787 | 600 | 0.4346 | 0.3190 |
| 0.1786 | 1.9722 | 800 | 0.4038 | 0.3424 |
| 0.0973 | 2.4639 | 1000 | 0.4064 | 0.2505 |
| 0.1057 | 2.9574 | 1200 | 0.3866 | 0.4107 |
| 0.0424 | 3.4491 | 1400 | 0.4073 | 0.2392 |
| 0.0591 | 3.9426 | 1600 | 0.4015 | 0.3277 |
| 0.0348 | 4.4343 | 1800 | 0.4354 | 0.2392 |
| 0.0273 | 4.9278 | 2000 | 0.4299 | 0.2165 |
Framework versions
- Transformers 4.53.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.0