metadata
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: openai/whisper-large-v2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: es
split: test
args: es
metrics:
- name: Wer
type: wer
value: 5.022549830956459
openai/whisper-large-v2
This model is a fine-tuned version of openai/whisper-large-v2 on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2657
- Wer: 5.0225
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 |
|---|---|---|---|---|
| 0.0869 | 2.0 | 1000 | 0.1754 | 6.1516 |
| 0.0913 | 4.0 | 2000 | 0.1652 | 5.7500 |
| 0.051 | 6.0 | 3000 | 0.1643 | 5.7757 |
| 0.0391 | 8.0 | 4000 | 0.1881 | 5.6589 |
| 0.0104 | 10.0 | 5000 | 0.2026 | 5.6211 |
| 0.0806 | 12.01 | 6000 | 0.1741 | 5.7398 |
| 0.0077 | 14.01 | 7000 | 0.2119 | 5.6038 |
| 0.0357 | 16.01 | 8000 | 0.1776 | 5.6147 |
| 0.1087 | 18.01 | 9000 | 0.1868 | 5.5172 |
| 0.0401 | 20.01 | 10000 | 0.2014 | 5.4428 |
| 0.0334 | 22.01 | 11000 | 0.1751 | 5.2824 |
| 0.0071 | 24.01 | 12000 | 0.2295 | 5.2490 |
| 0.0374 | 26.01 | 13000 | 0.2098 | 5.2574 |
| 0.0023 | 28.01 | 14000 | 0.2498 | 5.0418 |
| 0.0025 | 30.01 | 15000 | 0.2311 | 4.9385 |
| 0.0006 | 32.01 | 16000 | 0.2544 | 4.8949 |
| 0.0009 | 34.02 | 17000 | 0.2691 | 5.1246 |
| 0.003 | 36.02 | 18000 | 0.2249 | 5.0277 |
| 0.0009 | 38.02 | 19000 | 0.2603 | 5.0373 |
| 0.0008 | 40.02 | 20000 | 0.2657 | 5.0225 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3