metadata
license: apache-2.0
base_model: openai/whisper-large
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: openai/whisper-large
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: gl
split: test
args: gl
metrics:
- name: Wer
type: wer
value: 6.939845474613686
openai/whisper-large
This model is a fine-tuned version of openai/whisper-large on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3605
- Wer: 6.9398
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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0126 | 4.01 | 1000 | 0.2128 | 8.3558 |
| 0.0032 | 9.01 | 2000 | 0.2262 | 6.9416 |
| 0.0022 | 14.01 | 3000 | 0.2528 | 7.1123 |
| 0.0025 | 19.01 | 4000 | 0.2643 | 7.3641 |
| 0.0015 | 24.01 | 5000 | 0.2596 | 7.3365 |
| 0.0014 | 29.01 | 6000 | 0.2723 | 7.6366 |
| 0.0008 | 34.01 | 7000 | 0.2778 | 7.6090 |
| 0.0003 | 39.01 | 8000 | 0.2880 | 7.2261 |
| 0.0004 | 44.01 | 9000 | 0.2920 | 7.6745 |
| 0.0001 | 49.01 | 10000 | 0.2854 | 7.4089 |
| 0.0 | 54.01 | 11000 | 0.3027 | 7.4365 |
| 0.0 | 59.01 | 12000 | 0.3159 | 7.4055 |
| 0.0 | 64.01 | 13000 | 0.3242 | 7.3693 |
| 0.0 | 69.01 | 14000 | 0.3312 | 7.3072 |
| 0.0 | 74.01 | 15000 | 0.3379 | 7.0226 |
| 0.0 | 79.01 | 16000 | 0.3442 | 7.0019 |
| 0.0 | 84.01 | 17000 | 0.3500 | 6.9933 |
| 0.0 | 89.01 | 18000 | 0.3550 | 6.9605 |
| 0.0 | 94.01 | 19000 | 0.3589 | 6.9467 |
| 0.0 | 99.01 | 20000 | 0.3605 | 6.9398 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3