---
language:
- et
license: apache-2.0
base_model: openai/whisper-small
tags:
- audio
- asr
- automatic-speech-recognition
- hf-asr-leaderboard
model-index:
- name: whisper-small-smj
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# whisper-small-smj

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the NbAiLab/salmon-asr-smj dataset.
It achieves the following results on the evaluation set:
- step: 9999
- validation_loss: 0.3690
- train_loss: 0.2159
- validation_wer: 19.6809
- validation_cer: 5.5037
- validation_exact_wer: 22.3404
- validation_exact_cer: 5.8753

## 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: 5e-05
- lr_scheduler_type: linear
- per_device_train_batch_size: 32
- total_train_batch_size_per_node: 256
- total_train_batch_size: 256
- total_optimization_steps: 10,000
- starting_optimization_step: None
- finishing_optimization_step: 10,000
- num_train_dataset_workers: 32
- num_hosts: 1
- total_num_training_examples: 2,560,000
- steps_per_epoch: 70
- num_beams: None
- weight_decay: 0.01
- adam_beta1: 0.9
- adam_beta2: 0.98
- adam_epsilon: 1e-06
- dropout: True
- bpe_dropout_probability: 0.2
- activation_dropout_probability: 0.1

### Training results

| step | validation_loss | train_loss | validation_wer | validation_cer | validation_exact_wer | validation_exact_cer |
|:----:|:---------------:|:----------:|:--------------:|:--------------:|:--------------------:|:--------------------:|
| 0    | 3.4458          | 4.7979     | 205.7181       | 94.0902        | 150.2660             | 95.4591              |
| 1000 | 0.8415          | 0.2440     | 21.9415        | 6.4379         | 25.9309              | 7.0106               |
| 2000 | 1.0741          | 0.2249     | 21.6755        | 5.7474         | 25.0                 | 6.1741               |
| 3000 | 0.8933          | 0.2919     | 20.4787        | 5.3615         | 23.9362              | 5.8156               |
| 4000 | 0.8445          | 0.1339     | 18.8830        | 5.2193         | 21.4096              | 5.6363               |
| 5000 | 0.3739          | 0.2289     | 20.0798        | 5.3818         | 23.2713              | 5.8355               |
| 6000 | 0.3746          | 0.2586     | 19.8138        | 5.2600         | 22.7394              | 5.6562               |
| 7000 | 0.3555          | 0.2273     | 19.2819        | 5.7067         | 22.3404              | 6.0745               |
| 8000 | 0.3671          | 0.1632     | 19.4149        | 5.4224         | 22.3404              | 5.8952               |
| 9000 | 0.3508          | 0.2107     | 18.3511        | 5.3006         | 21.2766              | 5.7160               |
| 9999 | 0.3690          | 0.2159     | 19.6809        | 5.5037         | 22.3404              | 5.8753               |


### Framework versions

- Transformers 4.34.1
- Datasets 2.14.5
- Tokenizers 0.14.1