---
library_name: transformers
language:
- ro
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- custom
model-index:
- name: Whisper Large v3 RO - finetune
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Large v3 RO - finetune

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the custom 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 256
- optimizer: Use OptimizerNames.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: 10
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.48.0
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2