metadata
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-med-LoRA_FAA_data_small
results: []
whisper-med-LoRA_FAA_data_small
This model is a fine-tuned version of openai/whisper-medium on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.4632
- Wer: 56.9444
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
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.4359 | 1.0 | 1 | 4.5014 | 56.9444 |
| 4.4359 | 2.0 | 2 | 4.5014 | 56.9444 |
| 4.4359 | 3.0 | 3 | 4.5496 | 56.9444 |
| 4.458 | 4.0 | 4 | 4.5496 | 56.9444 |
| 4.4576 | 5.0 | 5 | 4.5439 | 56.9444 |
| 4.4411 | 6.0 | 6 | 4.4745 | 56.9444 |
| 4.4139 | 7.0 | 7 | 4.4745 | 56.9444 |
| 4.4166 | 8.0 | 8 | 4.4745 | 56.9444 |
| 4.4181 | 9.0 | 9 | 4.4722 | 56.9444 |
| 4.379 | 10.0 | 10 | 4.4632 | 56.9444 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3