metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- swagen
metrics:
- wer
model-index:
- name: whisper-medium-swagen-male-5hrs-42
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: swagen
type: swagen
metrics:
- name: Wer
type: wer
value: 0.3104715248009798
whisper-medium-swagen-male-5hrs-42
This model is a fine-tuned version of openai/whisper-medium on the swagen dataset. It achieves the following results on the evaluation set:
- Loss: 0.5428
- Wer: 0.3105
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 |
|---|---|---|---|---|
| 0.6796 | 0.4840 | 200 | 0.7989 | 0.4599 |
| 0.5052 | 0.9679 | 400 | 0.6415 | 0.3811 |
| 0.2656 | 1.4501 | 600 | 0.6006 | 0.3754 |
| 0.2673 | 1.9341 | 800 | 0.5640 | 0.3127 |
| 0.1119 | 2.4162 | 1000 | 0.5842 | 0.2986 |
| 0.1332 | 2.9002 | 1200 | 0.5428 | 0.3105 |
| 0.0484 | 3.3823 | 1400 | 0.5926 | 0.2809 |
| 0.051 | 3.8663 | 1600 | 0.5963 | 0.3184 |
| 0.0297 | 4.3485 | 1800 | 0.5950 | 0.3115 |
| 0.0223 | 4.8324 | 2000 | 0.6172 | 0.2841 |
Framework versions
- Transformers 4.53.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.0