metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- bigcgen
metrics:
- wer
model-index:
- name: whisper-medium-bigcgen-male-5hrs-model
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: bigcgen
type: bigcgen
metrics:
- name: Wer
type: wer
value: 0.5054099543159414
whisper-medium-bigcgen-male-5hrs-model
This model is a fine-tuned version of openai/whisper-medium on the bigcgen dataset. It achieves the following results on the evaluation set:
- Loss: 0.6817
- Wer: 0.5054
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: 1.75e-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
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.6678 | 0.6211 | 200 | 0.8233 | 0.6018 |
| 2.3045 | 1.2422 | 400 | 0.7233 | 0.6420 |
| 2.7509 | 1.8634 | 600 | 0.6881 | 0.5239 |
| 1.7043 | 2.4845 | 800 | 0.6817 | 0.5054 |
| 0.8068 | 3.1056 | 1000 | 0.7271 | 0.4915 |
| 0.9957 | 3.7267 | 1200 | 0.7331 | 0.4893 |
| 0.3976 | 4.3478 | 1400 | 0.7714 | 0.4943 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0