Edit model card

Whisper Small Ro - Sarbu Vlad - multi gpu --> 3

This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 + Romanian speech synthesis dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1249
  • Wer: 10.5571

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: 16
  • eval_batch_size: 10
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 3
  • total_train_batch_size: 48
  • total_eval_batch_size: 30
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 600
  • training_steps: 6000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2432 0.68 500 0.2134 19.7435
0.137 1.36 1000 0.1532 15.5189
0.0672 2.04 1500 0.1287 13.0426
0.0579 2.72 2000 0.1218 12.8659
0.0307 3.4 2500 0.1183 11.9887
0.0167 4.08 3000 0.1177 11.5866
0.016 4.76 3500 0.1149 10.9531
0.0099 5.43 4000 0.1212 10.9713
0.0058 6.11 4500 0.1216 10.8251
0.0056 6.79 5000 0.1224 10.6515
0.0036 7.47 5500 0.1238 10.6211
0.0035 8.15 6000 0.1249 10.5571

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.2.0
  • Datasets 2.17.0
  • Tokenizers 0.15.1
Downloads last month
2
Safetensors
Model size
282M params
Tensor type
FP16
·
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 VladS159/Whisper_small_ro_VladS_6000_steps_multi-gpu_28_05_2024

Finetuned
(1944)
this model

Dataset used to train VladS159/Whisper_small_ro_VladS_6000_steps_multi-gpu_28_05_2024

Evaluation results

  • Wer on Common Voice 17.0 + Romanian speech synthesis
    self-reported
    10.557