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metadata
language:
  - sl
license: apache-2.0
base_model: openai/whisper-small
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
model-index:
  - name: Whisper Small Sl - samolego
    results: []

Whisper Small Sl - samolego

This model is a fine-tuned version of openai/whisper-small on the ASR database ARTUR 1.0 (audio) dataset. It was trained on Artur-B-brani and Artur-B-Studio. It achieves the following results on the evaluation set:

  • Loss: 0.1226
  • Wer: 11.0097

Model description

Both ggml and safetensors formats are available.

If you're not familiar with ggml, I'd suggest checking out whisper.cpp.

Intended uses & limitations

More information needed

Training and evaluation data

Verdonik, Darinka; et al., 2023, ASR database ARTUR 1.0 (audio), Slovenian language resource repository CLARIN.SI, ISSN 2820-4042, http://hdl.handle.net/11356/1776.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss Wer
0.2778 0.07 500 0.2748 23.0421
0.2009 0.14 1000 0.1972 17.3073
0.1643 0.21 1500 0.1658 14.5195
0.1569 0.28 2000 0.1495 13.1550
0.1344 0.36 2500 0.1380 12.2945
0.1295 0.43 3000 0.1302 11.6237
0.1239 0.5 3500 0.1249 11.2128
0.1178 0.57 4000 0.1226 11.0097

Framework versions

  • Transformers 4.39.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.18.0
  • Tokenizers 0.15.2