metadata
base_model: openai/whisper-large-v3
datasets:
- google/fleurs
library_name: transformers
license: apache-2.0
metrics:
- wer
model-index:
- name: whisper-large-v3-Telugu-Version1
results: []
language:
- te
pipeline_tag: automatic-speech-recognition
whisper-large-v3-Telugu-Version1
This model is a fine-tuned version of openai/whisper-large-v3 on the fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.1610
- Wer: 48.7241
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: 3e-06
- train_batch_size: 8
- 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: 2000
- training_steps: 20000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2337 | 6.1920 | 2000 | 0.2242 | 61.4168 |
| 0.1902 | 12.3839 | 4000 | 0.1904 | 55.2632 |
| 0.169 | 18.5759 | 6000 | 0.1778 | 52.8575 |
| 0.1647 | 24.7678 | 8000 | 0.1710 | 51.6746 |
| 0.1523 | 30.9598 | 10000 | 0.1669 | 50.3589 |
| 0.1383 | 37.1517 | 12000 | 0.1642 | 49.9468 |
| 0.1561 | 43.3437 | 14000 | 0.1628 | 49.3089 |
| 0.1475 | 49.5356 | 16000 | 0.1616 | 48.9234 |
| 0.1437 | 55.7276 | 18000 | 0.1610 | 48.7241 |
| 0.1395 | 61.9195 | 20000 | 0.1610 | 48.7241 |
Framework versions
- PEFT 0.12.1.dev0
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1