metadata
library_name: transformers
language:
- lv
license: apache-2.0
base_model: FelixK7/whisper-medium-lv-ver2
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_0
metrics:
- wer
model-index:
- name: Whisper medium LV - Felikss Kleins
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 16.0
type: mozilla-foundation/common_voice_16_0
config: lv
split: None
args: 'config: lv, split: test'
metrics:
- name: Wer
type: wer
value: 19.39252336448598
Whisper medium LV - Felikss Kleins
This model is a fine-tuned version of FelixK7/whisper-medium-lv-ver2 on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2882
- Wer: 19.3925
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
No log | 99.0002 | 200 | 0.1666 | 11.4486 |
0.0028 | 199.0002 | 400 | 0.2083 | 13.5514 |
0.0007 | 299.0002 | 600 | 0.2815 | 20.7944 |
0.0008 | 399.0002 | 800 | 0.2882 | 19.3925 |
Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.0.1
- Datasets 3.0.1
- Tokenizers 0.20.1