metadata
language:
- mar
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: whisper_marathi_small_V1
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: mr
split: test
args: 'config: hi, split: test'
metrics:
- name: Wer
type: wer
value: 45.00676938946554
whisper_marathi_small_V1
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2754
- Wer: 45.0068
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: 10
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4794 | 0.41 | 100 | 0.4754 | 59.9317 |
| 0.3121 | 0.81 | 200 | 0.3161 | 52.8786 |
| 0.2051 | 1.22 | 300 | 0.2900 | 50.2547 |
| 0.1887 | 1.63 | 400 | 0.2779 | 48.1336 |
| 0.16 | 2.03 | 500 | 0.2679 | 46.2639 |
| 0.1131 | 2.44 | 600 | 0.2706 | 45.8449 |
| 0.1128 | 2.85 | 700 | 0.2658 | 45.1551 |
| 0.0678 | 3.25 | 800 | 0.2763 | 45.2195 |
| 0.075 | 3.66 | 900 | 0.2769 | 45.7611 |
| 0.0609 | 4.07 | 1000 | 0.2754 | 45.0068 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2