---
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
model-index:
- name: whisper-large-final
  results: []
language:
- mn
---

<!-- 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-final

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co./openai/whisper-large-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0112
- eval_wer: 1.1712
- eval_runtime: 982.7637
- eval_samples_per_second: 1.892
- eval_steps_per_second: 0.237
- epoch: 6.4205
- step: 4000

## Model description

Step	Training Loss	Validation Loss	Wer
500	0.431500	0.412413	48.265244
1000	0.244500	0.230148	29.284654
1500	0.134300	0.122366	16.588772
2000	0.055800	0.069241	10.551493
2500	0.045700	0.035967	4.860615
3000	0.027900	0.024117	3.425524
3500	0.011000	0.016053	1.770495
4000	0.004800	0.011227	1.171166

## 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: 1000
- training_steps: 5000
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.0
- Datasets 2.19.1
- Tokenizers 0.19.1