Edit model card

Fauna-v3.3 - Rootflo

This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0704
  • Wer: 26.2284

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: 2e-06
  • train_batch_size: 96
  • eval_batch_size: 96
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 768
  • total_eval_batch_size: 384
  • optimizer: Use adamw_bnb_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 50
  • training_steps: 0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2281 1.0 460 0.1114 35.7178
0.1647 2.0 920 0.0913 31.4522
0.1418 3.0 1380 0.0819 29.2863
0.1222 4.0 1840 0.0766 28.2008
0.1136 5.0 2300 0.0728 26.6919
0.1077 6.0 2760 0.0712 26.3193
0.104 7.0 3220 0.0705 129.6359
0.1028 8.0 3680 0.0704 26.2284

Framework versions

  • Transformers 4.46.1
  • Pytorch 2.5.1+cu124
  • Datasets 3.0.2
  • Tokenizers 0.20.3
Downloads last month
6
Safetensors
Model size
1.54B params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for vizsatiz/fauna-v3.3

Finetuned
(309)
this model