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-female-model
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: swagen
type: swagen
metrics:
- name: Wer
type: wer
value: 0.33982266769468006
whisper-medium-swagen-female-model
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: 0.5405
- Wer: 0.3398
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use 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 |
|---|---|---|---|---|
| 1.4291 | 0.4700 | 200 | 0.8217 | 0.4967 |
| 0.9176 | 0.9401 | 400 | 0.6348 | 0.4266 |
| 0.5492 | 1.4089 | 600 | 0.5868 | 0.4094 |
| 0.6243 | 1.8790 | 800 | 0.5535 | 0.3275 |
| 0.2196 | 2.3478 | 1000 | 0.5643 | 0.3577 |
| 0.2211 | 2.8179 | 1200 | 0.5405 | 0.3398 |
| 0.0999 | 3.2867 | 1400 | 0.5826 | 0.3283 |
| 0.1111 | 3.7568 | 1600 | 0.5537 | 0.3277 |
| 0.0423 | 4.2256 | 1800 | 0.6012 | 0.3188 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0