---
license: apache-2.0
base_model: openai/whisper-large
tags:
- generated_from_trainer
datasets:
- ravnursson_asr
metrics:
- wer
model-index:
- name: whisper-large-fo-100h-30k-steps
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: ravnursson_asr
      type: ravnursson_asr
      config: ravnursson_asr
      split: test
      args: ravnursson_asr
    metrics:
    - name: Wer
      type: wer
      value: 4.957720958324945
---

<!-- 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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/setur/huggingface/runs/woejhwzd)
# whisper-large-fo-100h-30k-steps

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the ravnursson_asr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0872
- Wer: 4.9577

## 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: 30000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.2261        | 0.2320 | 1000  | 0.2668          | 20.1379 |
| 0.1577        | 0.4640 | 2000  | 0.1840          | 15.0997 |
| 0.1205        | 0.6961 | 3000  | 0.1456          | 11.9489 |
| 0.1151        | 0.9281 | 4000  | 0.1300          | 10.6906 |
| 0.0457        | 1.1601 | 5000  | 0.1241          | 9.7745  |
| 0.0423        | 1.3921 | 6000  | 0.1221          | 9.4876  |
| 0.0428        | 1.6241 | 7000  | 0.1080          | 8.4709  |
| 0.0486        | 1.8561 | 8000  | 0.1053          | 8.5011  |
| 0.0205        | 2.0882 | 9000  | 0.1014          | 7.4643  |
| 0.0184        | 2.3202 | 10000 | 0.1003          | 8.1387  |
| 0.0165        | 2.5522 | 11000 | 0.0969          | 7.1472  |
| 0.025         | 2.7842 | 12000 | 0.0907          | 6.8804  |
| 0.0048        | 3.0162 | 13000 | 0.0936          | 6.9005  |
| 0.0092        | 3.2483 | 14000 | 0.0923          | 6.7244  |
| 0.006         | 3.4803 | 15000 | 0.0921          | 6.3519  |
| 0.0095        | 3.7123 | 16000 | 0.0922          | 6.3821  |
| 0.0089        | 3.9443 | 17000 | 0.0929          | 6.3771  |
| 0.0023        | 4.1763 | 18000 | 0.0915          | 6.0650  |
| 0.0033        | 4.4084 | 19000 | 0.0924          | 5.9543  |
| 0.0028        | 4.6404 | 20000 | 0.0909          | 5.9040  |
| 0.0021        | 4.8724 | 21000 | 0.0884          | 5.7328  |
| 0.002         | 5.1044 | 22000 | 0.0874          | 5.4057  |
| 0.0008        | 5.3364 | 23000 | 0.0890          | 5.3654  |
| 0.0005        | 5.5684 | 24000 | 0.0857          | 5.2597  |
| 0.002         | 5.8005 | 25000 | 0.0860          | 5.2144  |
| 0.0007        | 6.0325 | 26000 | 0.0873          | 5.1842  |
| 0.0002        | 6.2645 | 27000 | 0.0850          | 4.9879  |
| 0.001         | 6.4965 | 28000 | 0.0889          | 4.9376  |
| 0.0001        | 6.7285 | 29000 | 0.0878          | 5.0081  |
| 0.0003        | 6.9606 | 30000 | 0.0872          | 4.9577  |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1