metadata
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
model-index:
- name: whisper-large-final
results: []
language:
- mn
whisper-large-final
This model is a fine-tuned version of openai/whisper-large-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.0112
- eval_wer: 1.1712
- eval_runtime: 982.7637
- eval_samples_per_second: 1.892
- eval_steps_per_second: 0.237
- epoch: 6.4205
- step: 4000
Model description
Step Training Loss Validation Loss Wer 500 0.431500 0.412413 48.265244 1000 0.244500 0.230148 29.284654 1500 0.134300 0.122366 16.588772 2000 0.055800 0.069241 10.551493 2500 0.045700 0.035967 4.860615 3000 0.027900 0.024117 3.425524 3500 0.011000 0.016053 1.770495 4000 0.004800 0.011227 1.171166
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: 8
- 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: 5000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.0
- Datasets 2.19.1
- Tokenizers 0.19.1