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---
language:
- mn
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Large MN - Ankhbayasgalan Davaadorj
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 16.1 & FLEURS
type: mozilla-foundation/common_voice_16_1
config: mn
split: None
args: 'config: mn, split: test+validation'
metrics:
- name: Wer
type: wer
value: 33.65601452065343
---
<!-- 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 MN - Ankhbayasgalan Davaadorj
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Common Voice 16.1 & FLEURS dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4942
- Wer: 33.6560
## 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0361 | 5.99 | 1000 | 0.3833 | 42.0109 |
| 0.0016 | 11.98 | 2000 | 0.4445 | 37.2092 |
| 0.0002 | 17.96 | 3000 | 0.4784 | 34.0410 |
| 0.0001 | 23.95 | 4000 | 0.4942 | 33.6560 |
### Framework versions
- Transformers 4.37.2
- Pytorch 1.12.1+cu116
- Datasets 2.17.0
- Tokenizers 0.15.2
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