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---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- wjbmattingly/zulu_merged_audio
metrics:
- wer
model-index:
- name: whisper-zulu-medium
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: wjbmattingly/zulu_merged_audio
type: wjbmattingly/zulu_merged_audio
metrics:
- name: Wer
type: wer
value: 0.1993037098042152
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# whisper-zulu-medium
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the wjbmattingly/zulu_merged_audio dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2949
- Wer: 0.1993
## 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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 400
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.8378 | 1.25 | 100 | 0.7290 | 0.5605 |
| 0.3624 | 2.5 | 200 | 0.4048 | 0.2791 |
| 0.2279 | 3.75 | 300 | 0.3236 | 0.2187 |
| 0.1524 | 5.0 | 400 | 0.2949 | 0.1993 |
### Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.21.0
- Tokenizers 0.19.1
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