---
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
datasets:
- ravnursson_asr
metrics:
- wer
model-index:
- name: whisper-large-v2-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: 4.9124219851016715
---

<!-- 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/og6v8hvi)
# whisper-large-v2-fo-100h-30k-steps

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the ravnursson_asr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0837
- Wer: 4.9124

## 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     |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.2336        | 0.2320 | 1000  | 0.2811          | 20.5154 |
| 0.1631        | 0.4640 | 2000  | 0.1950          | 15.0191 |
| 0.124         | 0.6961 | 3000  | 0.1548          | 12.6334 |
| 0.1234        | 0.9281 | 4000  | 0.1323          | 11.0077 |
| 0.0568        | 1.1601 | 5000  | 0.1257          | 10.2174 |
| 0.0493        | 1.3921 | 6000  | 0.1204          | 9.5380  |
| 0.0473        | 1.6241 | 7000  | 0.1123          | 9.2158  |
| 0.0489        | 1.8561 | 8000  | 0.1012          | 8.1588  |
| 0.0193        | 2.0882 | 9000  | 0.0983          | 7.7159  |
| 0.0242        | 2.3202 | 10000 | 0.0933          | 7.1522  |
| 0.0171        | 2.5522 | 11000 | 0.0939          | 7.2680  |
| 0.0277        | 2.7842 | 12000 | 0.0876          | 7.0364  |
| 0.0077        | 3.0162 | 13000 | 0.0890          | 6.2563  |
| 0.0102        | 3.2483 | 14000 | 0.0883          | 6.9609  |
| 0.0089        | 3.4803 | 15000 | 0.0871          | 6.2110  |
| 0.0119        | 3.7123 | 16000 | 0.0854          | 6.4425  |
| 0.0109        | 3.9443 | 17000 | 0.0839          | 5.7379  |
| 0.0026        | 4.1763 | 18000 | 0.0850          | 5.9946  |
| 0.0063        | 4.4084 | 19000 | 0.0878          | 5.9644  |
| 0.0039        | 4.6404 | 20000 | 0.0896          | 6.2966  |
| 0.0038        | 4.8724 | 21000 | 0.0842          | 5.9895  |
| 0.0028        | 5.1044 | 22000 | 0.0811          | 5.7026  |
| 0.0021        | 5.3364 | 23000 | 0.0828          | 5.2194  |
| 0.0009        | 5.5684 | 24000 | 0.0850          | 5.1792  |
| 0.0023        | 5.8005 | 25000 | 0.0826          | 5.1188  |
| 0.0005        | 6.0325 | 26000 | 0.0823          | 5.0936  |
| 0.0004        | 6.2645 | 27000 | 0.0818          | 4.9225  |
| 0.0017        | 6.4965 | 28000 | 0.0839          | 4.9980  |
| 0.0002        | 6.7285 | 29000 | 0.0843          | 4.9577  |
| 0.0004        | 6.9606 | 30000 | 0.0837          | 4.9124  |


### Framework versions

- Transformers 4.43.1
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1