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End of training
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---
library_name: transformers
language:
- qve
license: apache-2.0
base_model: openai/whisper-large
tags:
- generated_from_trainer
datasets:
- cportoca/Quechua_Spanish_dataset
model-index:
- name: Whisper Large Es-Qve - cportoca
results: []
---
<!-- 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 Large Es-Qve - cportoca
This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the Quechua_Spanish_dataset dataset.
## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8000
- mixed_precision_training: Native AMP
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3