metadata
language:
- cs
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper tiny Czech CV13 v1
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_13_0 cs
type: mozilla-foundation/common_voice_13_0
config: cs
split: test
args: cs
metrics:
- name: Wer
type: wer
value: 44.080171349061175
Whisper tiny Czech CV13 v1
This model is a fine-tuned version of openai/whisper-tiny on the mozilla-foundation/common_voice_13_0 cs dataset. It achieves the following results on the evaluation set:
- Loss: 0.5430
- Wer: 44.0802
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
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 4
- total_train_batch_size: 384
- total_eval_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 3000
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1007 | 21.86 | 1000 | 0.5430 | 44.0802 |
0.013 | 43.72 | 2000 | 0.6489 | 44.9182 |
0.0079 | 65.57 | 3000 | 0.6782 | 45.5169 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3