metadata
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: []
whisper-small-smj
This model is a fine-tuned version of openai/whisper-small on the NbAiLab/salmon-asr-smj dataset.
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 |
Framework versions
- Transformers 4.34.1
- Datasets 2.14.5
- Tokenizers 0.14.1