metadata
language:
- cs
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-large-v2
model-index:
- name: Whisper Large-v2 Czech CV11 v2
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0 cs
type: mozilla-foundation/common_voice_11_0
config: cs
split: test
args: cs
metrics:
- type: wer
value: 9.045873924973758
name: Wer
Whisper Large-v2 Czech CV11 v2
This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_11_0 cs dataset. It achieves the following results on the evaluation set:
- Loss: 0.2120
- Wer: 9.0459
Model description
Fine tuned with deepspeed optimization and batch_size: 32.
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: 8
- seed: 42
- distributed_type: multi-GPU
- 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: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0106 | 4.24 | 1000 | 0.1625 | 9.9888 |
| 0.0034 | 8.47 | 2000 | 0.1841 | 9.8304 |
| 0.0011 | 12.71 | 3000 | 0.1917 | 9.4031 |
| 0.0004 | 16.95 | 4000 | 0.2075 | 9.1177 |
| 0.0003 | 21.19 | 5000 | 0.2120 | 9.0459 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2