metadata

language:
  - lv
license: apache-2.0
base_model: arturslogins/whisper-medium-lv
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - ta-dataset/training
metrics:
  - wer
model-index:
  - name: Whisper medium LV - Arturs Logins
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Recorded Voice
          type: ta-dataset/training
          config: lv
          split: test
          args: 'config: lv, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 44.06162804804076

Whisper medium LV - Arturs Logins

This model is a fine-tuned version of arturslogins/whisper-medium-lv on the Recorded Voice dataset. It achieves the following results on the evaluation set:

Loss: 1.1246
Wer: 44.0616

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: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0175	6.4	1000	0.9442	45.7358
0.0043	12.8	2000	0.9789	45.6994
0.0012	19.2	3000	1.0763	47.4221
0.0001	25.6	4000	1.1194	44.1708
0.0001	32.0	5000	1.1246	44.0616

Framework versions

Transformers 4.41.0.dev0
Pytorch 2.0.1
Datasets 2.19.0
Tokenizers 0.19.1