metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- toigen
metrics:
- wer
model-index:
- name: whisper-medium-toigen-combined-model
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: toigen
type: toigen
metrics:
- name: Wer
type: wer
value: 0.4497528830313015
whisper-medium-toigen-combined-model
This model is a fine-tuned version of openai/whisper-medium on the toigen dataset. It achieves the following results on the evaluation set:
- Loss: 0.6425
- Wer: 0.4498
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 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
- num_epochs: 30.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.9586 | 0.9467 | 200 | 0.8733 | 0.5994 |
| 2.4999 | 1.8899 | 400 | 0.6726 | 0.4648 |
| 1.7047 | 2.8331 | 600 | 0.6523 | 0.4585 |
| 0.9573 | 3.7763 | 800 | 0.6425 | 0.4498 |
| 0.4029 | 4.7195 | 1000 | 0.6657 | 0.4043 |
| 0.2311 | 5.6627 | 1200 | 0.6910 | 0.4187 |
| 0.1545 | 6.6059 | 1400 | 0.7208 | 0.3864 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0