metadata
language:
- hi
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- konnakol
metrics:
- wer
model-index:
- name: Whisper Hi - Gopika
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Konnakol
type: konnakol
args: 'config: hi, split: test'
metrics:
- name: Wer
type: wer
value: 0.026845637583892617
Whisper Hi - Gopika
This model is a fine-tuned version of openai/whisper-medium on the Konnakol dataset. It achieves the following results on the evaluation set:
- Loss: 0.2424
- Wer: 0.0268
- Cer: 0.0281
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 16
- 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: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 2.6928 | 8.3333 | 50 | 0.7108 | 0.0593 | 0.0502 |
| 0.1456 | 16.6667 | 100 | 0.1978 | 0.0503 | 0.0448 |
| 0.0104 | 25.0 | 150 | 0.1970 | 0.0291 | 0.0293 |
| 0.0145 | 33.3333 | 200 | 0.2114 | 0.0503 | 0.0387 |
| 0.0123 | 41.6667 | 250 | 0.2174 | 0.0515 | 0.0511 |
| 0.0086 | 50.0 | 300 | 0.2339 | 0.0246 | 0.0263 |
| 0.0077 | 58.3333 | 350 | 0.2737 | 0.0336 | 0.0303 |
| 0.0132 | 66.6667 | 400 | 0.1764 | 0.0268 | 0.0269 |
| 0.005 | 75.0 | 450 | 0.2107 | 0.0336 | 0.0339 |
| 0.0207 | 83.3333 | 500 | 0.2167 | 0.4955 | 0.4702 |
| 0.0153 | 91.6667 | 550 | 0.1948 | 0.0358 | 0.0342 |
| 0.013 | 100.0 | 600 | 0.1882 | 0.0257 | 0.0230 |
| 0.001 | 108.3333 | 650 | 0.2405 | 0.0302 | 0.0324 |
| 0.0018 | 116.6667 | 700 | 0.2377 | 0.0302 | 0.0290 |
| 0.0 | 125.0 | 750 | 0.2385 | 0.0268 | 0.0281 |
| 0.0 | 133.3333 | 800 | 0.2398 | 0.0268 | 0.0281 |
| 0.0 | 141.6667 | 850 | 0.2409 | 0.0268 | 0.0281 |
| 0.0 | 150.0 | 900 | 0.2418 | 0.0268 | 0.0281 |
| 0.0 | 158.3333 | 950 | 0.2422 | 0.0268 | 0.0281 |
| 0.0 | 166.6667 | 1000 | 0.2424 | 0.0268 | 0.0281 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1