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: gl
split: test
args: gl
metrics:
- name: Wer
type: wer
value: 6.01717715231788
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: 0.3753
- Wer: 6.0172
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 |
|---|---|---|---|---|
| 0.0185 | 4.01 | 1000 | 0.1896 | 6.3569 |
| 0.0067 | 9.01 | 2000 | 0.2083 | 6.3862 |
| 0.0038 | 14.01 | 3000 | 0.2291 | 6.4621 |
| 0.0022 | 19.01 | 4000 | 0.2412 | 6.4794 |
| 0.0013 | 24.01 | 5000 | 0.2515 | 6.4673 |
| 0.0023 | 29.01 | 6000 | 0.2570 | 6.6432 |
| 0.0018 | 34.01 | 7000 | 0.2474 | 6.6380 |
| 0.0017 | 39.01 | 8000 | 0.2530 | 6.9312 |
| 0.0001 | 44.01 | 9000 | 0.2758 | 6.2379 |
| 0.0001 | 49.01 | 10000 | 0.2952 | 6.1241 |
| 0.0001 | 54.01 | 11000 | 0.3056 | 6.0499 |
| 0.0 | 59.01 | 12000 | 0.3152 | 5.9948 |
| 0.0 | 64.01 | 13000 | 0.3244 | 6.0310 |
| 0.0 | 69.01 | 14000 | 0.3336 | 6.0586 |
| 0.0 | 74.01 | 15000 | 0.3428 | 6.0344 |
| 0.0 | 79.01 | 16000 | 0.3518 | 6.0017 |
| 0.0 | 84.01 | 17000 | 0.3601 | 5.9879 |
| 0.0 | 89.01 | 18000 | 0.3675 | 6.0103 |
| 0.0 | 94.01 | 19000 | 0.3729 | 6.0068 |
| 0.0 | 99.01 | 20000 | 0.3753 | 6.0172 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3