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---
language:
- az
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-large-v2
model-index:
- name: Whisper Large v2 Azerbaijani
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0 az
type: mozilla-foundation/common_voice_11_0
config: az
split: test
args: az
metrics:
- type: wer
value: 38.46153846153847
name: Wer
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Large v2 Azerbaijani
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 az dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9435
- Wer: 38.4615
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.0 | 999.0 | 1000 | 0.8373 | 39.6450 |
| 0.0 | 1999.0 | 2000 | 0.9435 | 38.4615 |
| 0.0 | 2999.0 | 3000 | 1.0010 | 43.1953 |
| 0.0 | 3999.0 | 4000 | 1.0380 | 44.3787 |
| 0.0 | 4999.0 | 5000 | 1.0529 | 43.7870 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|