metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- fsicoli/common_voice_18_0
metrics:
- wer
model-index:
- name: Whisper Medium New Train
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 18.0
type: fsicoli/common_voice_18_0
metrics:
- name: Wer
type: wer
value: 2.2782892974889872
Whisper Medium New Train
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 18.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0204
- Wer: 2.2783
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 8000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2733 | 0.4077 | 1000 | 0.2585 | 32.5924 |
| 0.1527 | 0.8153 | 2000 | 0.1246 | 16.7238 |
| 0.0655 | 1.2230 | 3000 | 0.0776 | 10.5668 |
| 0.0455 | 1.6307 | 4000 | 0.0514 | 6.7675 |
| 0.0162 | 2.0383 | 5000 | 0.0353 | 4.4772 |
| 0.0129 | 2.4460 | 6000 | 0.0274 | 3.4364 |
| 0.0117 | 2.8536 | 7000 | 0.0220 | 2.5110 |
| 0.0044 | 3.2613 | 8000 | 0.0204 | 2.2783 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.3.1
- Datasets 3.0.0
- Tokenizers 0.19.1