---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v3
  results: []
---

<!-- 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-v3

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: 0.1965
- Wer Ortho: 18.1002
- Wer: 15.9525

## 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: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer Ortho | Wer      |
|:-------------:|:------:|:-----:|:---------------:|:---------:|:--------:|
| 0.6288        | 0.0952 | 500   | 0.6102          | 55.9280   | 60.8769  |
| 0.5324        | 0.1904 | 1000  | 0.5052          | 39.4707   | 42.5276  |
| 0.4501        | 0.2856 | 1500  | 0.4515          | 61.0459   | 54.8192  |
| 0.4097        | 0.3807 | 2000  | 0.4170          | 55.1628   | 61.1920  |
| 0.3907        | 0.4759 | 2500  | 0.3918          | 32.0076   | 28.6487  |
| 0.3647        | 0.5711 | 3000  | 0.3704          | 63.9223   | 100.4724 |
| 0.3832        | 0.6663 | 3500  | 0.3503          | 28.5079   | 24.8599  |
| 0.3584        | 0.7615 | 4000  | 0.3356          | 25.4798   | 21.6963  |
| 0.3358        | 0.8567 | 4500  | 0.3208          | 30.3739   | 23.8063  |
| 0.3157        | 0.9518 | 5000  | 0.3068          | 30.6595   | 24.0364  |
| 0.2682        | 1.0470 | 5500  | 0.2945          | 28.6989   | 31.7195  |
| 0.2809        | 1.1422 | 6000  | 0.2834          | 40.9943   | 42.9384  |
| 0.264         | 1.2374 | 6500  | 0.2726          | 21.4030   | 17.7449  |
| 0.231         | 1.3326 | 7000  | 0.2626          | 20.2943   | 16.7944  |
| 0.2162        | 1.4278 | 7500  | 0.2502          | 21.4164   | 18.6420  |
| 0.2581        | 1.5229 | 8000  | 0.2375          | 18.9646   | 20.5258  |
| 0.2395        | 1.6181 | 8500  | 0.2282          | 21.2771   | 17.5843  |
| 0.1951        | 1.7133 | 9000  | 0.2185          | 19.0834   | 15.9387  |
| 0.1733        | 1.8085 | 9500  | 0.2086          | 19.9144   | 18.8285  |
| 0.1896        | 1.9037 | 10000 | 0.1965          | 18.1002   | 15.9525  |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1