đ Whisper medium AT
This model is a fine - tuned version of openai/whisper - medium, which is used for automatic speech recognition on the AT_ENT dataset, achieving good results in evaluation.
đ Quick Start
This model is a fine - tuned version of openai/whisper - medium on the AT_ENT dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2100
- Wer: 66.8297
đ Documentation
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
Training Loss |
Epoch |
Step |
Validation Loss |
Wer |
No log |
1.0 |
111 |
1.0527 |
63.9374 |
No log |
2.0 |
222 |
1.0961 |
65.8796 |
No log |
3.0 |
333 |
1.1626 |
67.5283 |
No log |
4.0 |
444 |
1.2100 |
66.8297 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
đ License
The model is licensed under the apache - 2.0 license.
đĻ Model Information
Property |
Details |
Base Model |
openai/whisper - medium |
Datasets |
AT_ENT |
Language |
aeb |
Library Name |
transformers |
Metrics |
wer |
Tags |
generated_from_trainer |
Model Name |
Whisper medium AT |
Task Type |
automatic - speech - recognition |
Evaluation Dataset |
AT_ENT (config: aeb, split: test) |
Wer on Evaluation Set |
66.82967723906664 |