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---
library_name: transformers
language:
- ht
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- phatjmo/cmu_haitian
metrics:
- wer
model-index:
- name: Whisper Medium Ht - TranslateLive
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Carnegie Mellon University - Haitian Creole
type: phatjmo/cmu_haitian
args: 'config: ht, split: test'
metrics:
- name: Wer
type: wer
value: 19.04038870331005
---
<!-- 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 Medium Ht - TranslateLive
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Carnegie Mellon University - Haitian Creole dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7836
- Wer: 19.0404
## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0571 | 3.4483 | 1000 | 0.5976 | 21.8190 |
| 0.0037 | 6.8966 | 2000 | 0.7251 | 19.5136 |
| 0.0003 | 10.3448 | 3000 | 0.7623 | 19.4807 |
| 0.0005 | 13.7931 | 4000 | 0.7836 | 19.0404 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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