metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: whisper-small-hi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: hi
split: None
args: hi
metrics:
- name: Wer
type: wer
value: 56.70447811732837
whisper-small-hi
This model is a fine-tuned version of openai/whisper-tiny on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5378
- Wer: 56.7045
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.3147 | 2.4450 | 1000 | 0.5462 | 61.2969 |
0.1993 | 4.8900 | 2000 | 0.5212 | 57.2082 |
0.1321 | 7.3350 | 3000 | 0.5378 | 56.7045 |
Framework versions
- Transformers 4.41.2
- Pytorch 1.12.1
- Datasets 2.20.0
- Tokenizers 0.19.1