metadata
language:
- hi
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium Hindi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 hi
type: mozilla-foundation/common_voice_11_0
config: hi
split: test
args: hi
metrics:
- name: Wer
type: wer
value: 12.981869792143577
Whisper Medium Hindi
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_11_0 hi dataset. It achieves the following results on the evaluation set:
- Loss: 0.2306
- Wer: 12.9819
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: 2
- eval_batch_size: 1
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.218 | 0.2 | 1000 | 0.2970 | 20.1538 |
| 0.1537 | 0.4 | 2000 | 0.2573 | 17.2535 |
| 0.0802 | 1.16 | 3000 | 0.2392 | 14.2798 |
| 0.0521 | 1.36 | 4000 | 0.2263 | 13.7144 |
| 0.0135 | 2.13 | 5000 | 0.2306 | 12.9819 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2