Whisper Medium Ro - Sarbu Vlad - multi gpu
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 16.1 + Romanian speech synthesis dataset. It achieves the following results on the evaluation set:
- Loss: 0.0807
- Wer: 8.3506
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: 10
- eval_batch_size: 10
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- total_train_batch_size: 30
- 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: 200
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1753 | 0.22 | 250 | 0.1553 | 14.6629 |
0.1227 | 0.43 | 500 | 0.1203 | 11.8855 |
0.1286 | 0.65 | 750 | 0.1053 | 10.8999 |
0.1129 | 0.86 | 1000 | 0.0969 | 10.4557 |
0.051 | 1.08 | 1250 | 0.0882 | 9.1050 |
0.0589 | 1.3 | 1500 | 0.0851 | 9.0138 |
0.05 | 1.51 | 1750 | 0.0832 | 8.7795 |
0.0492 | 1.73 | 2000 | 0.0807 | 8.3506 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.17.0
- Tokenizers 0.15.1
- Downloads last month
- 5
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Model tree for VladS159/Whisper_medium_ro_VladS_2000_steps_multi_gpu_26_02_2024
Base model
openai/whisper-mediumDataset used to train VladS159/Whisper_medium_ro_VladS_2000_steps_multi_gpu_26_02_2024
Evaluation results
- Wer on Common Voice 16.1 + Romanian speech synthesisself-reported8.351