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---
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-meduim-mongolian
results: []
datasets:
- Cafet/whisper-mongolian-final
language:
- mn
library_name: transformers
pipeline_tag: automatic-speech-recognition
---
<!-- 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-meduim-mongolian
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3098
- Wer: 26.8664
## 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: 4
- 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: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.3034 | 0.9398 | 2000 | 0.4135 | 45.1152 |
| 0.1443 | 1.8797 | 4000 | 0.3127 | 35.3290 |
| 0.0618 | 2.8195 | 6000 | 0.3038 | 31.0534 |
| 0.0179 | 3.7594 | 8000 | 0.3042 | 28.3673 |
| 0.0028 | 4.6992 | 10000 | 0.3098 | 26.8664 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.2.0
- Datasets 2.19.0
- Tokenizers 0.19.1 |