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: eu
split: test
args: eu
metrics:
- name: Wer
type: wer
value: 12.234193365466401
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: 0.4369
- Wer: 12.2342
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 |
|---|---|---|---|---|
| 0.0196 | 4.01 | 1000 | 0.2825 | 15.4725 |
| 0.0039 | 9.01 | 2000 | 0.3072 | 14.2270 |
| 0.0031 | 14.01 | 3000 | 0.3170 | 13.7652 |
| 0.0023 | 19.0 | 4000 | 0.3310 | 13.6640 |
| 0.0014 | 24.0 | 5000 | 0.3384 | 13.5749 |
| 0.0034 | 29.0 | 6000 | 0.3425 | 13.7450 |
| 0.0011 | 33.01 | 7000 | 0.3476 | 13.0990 |
| 0.001 | 38.01 | 8000 | 0.3432 | 13.0990 |
| 0.0004 | 43.01 | 9000 | 0.3524 | 12.8033 |
| 0.0017 | 48.01 | 10000 | 0.3620 | 13.3946 |
| 0.0003 | 53.0 | 11000 | 0.3564 | 12.6190 |
| 0.0001 | 58.0 | 12000 | 0.3675 | 12.6352 |
| 0.0 | 63.0 | 13000 | 0.3878 | 12.4286 |
| 0.0 | 67.01 | 14000 | 0.3996 | 12.3577 |
| 0.0 | 72.01 | 15000 | 0.4088 | 12.3456 |
| 0.0 | 77.01 | 16000 | 0.4167 | 12.3091 |
| 0.0 | 82.01 | 17000 | 0.4241 | 12.3112 |
| 0.0 | 87.0 | 18000 | 0.4302 | 12.3193 |
| 0.0 | 92.0 | 19000 | 0.4351 | 12.2565 |
| 0.0 | 97.0 | 20000 | 0.4369 | 12.2342 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3