metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large
tags:
- generated_from_trainer
datasets:
- deepinfinityai/29_lines_robust_dataset
metrics:
- wer
model-index:
- name: v5_03_7Epochs_Robust_Model
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: 29 Lines
type: deepinfinityai/29_lines_robust_dataset
metrics:
- name: Wer
type: wer
value: 0
v5_03_7Epochs_Robust_Model
This model is a fine-tuned version of openai/whisper-large on the 29 Lines dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Wer: 0.0
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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 278
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3161 | 1.25 | 50 | 0.0173 | 2.0305 |
| 0.0121 | 2.5 | 100 | 0.0001 | 0.0 |
| 0.0005 | 3.75 | 150 | 0.0000 | 0.0 |
| 0.0 | 5.0 | 200 | 0.0000 | 0.0 |
| 0.0 | 6.25 | 250 | 0.0000 | 0.0 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0