metadata
language:
- tr
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Medium Tr - Can K V2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: tr
split: test
args: 'config: tr, split: test'
metrics:
- name: Wer
type: wer
value: 15.4185472196202
Whisper Medium Tr - Can K V2
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2285
- Wer: 15.4185
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: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 12000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.203 | 0.3448 | 1000 | 0.2255 | 19.4192 |
| 0.1602 | 0.6895 | 2000 | 0.2142 | 18.0448 |
| 0.0814 | 1.0343 | 3000 | 0.2087 | 17.5338 |
| 0.0761 | 1.3791 | 4000 | 0.2060 | 17.1558 |
| 0.0734 | 1.7238 | 5000 | 0.1998 | 16.5052 |
| 0.0335 | 2.0686 | 6000 | 0.2073 | 16.7283 |
| 0.0344 | 2.4134 | 7000 | 0.2066 | 15.9091 |
| 0.0338 | 2.7581 | 8000 | 0.2023 | 15.3709 |
| 0.0099 | 3.1029 | 9000 | 0.2211 | 15.6331 |
| 0.0097 | 3.4477 | 10000 | 0.2254 | 15.6008 |
| 0.0096 | 3.7924 | 11000 | 0.2254 | 15.3334 |
| 0.0022 | 4.1372 | 12000 | 0.2285 | 15.4185 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1