---
library_name: transformers
language:
- multilingual
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- whisper-event
- generated_from_trainer
metrics:
- bleu
model-index:
- name: Fauna-v3.6 - Rootflo
  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. -->

# Fauna-v3.6 - Rootflo

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1129
- Bleu: 19.6035

## 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: 2e-06
- train_batch_size: 96
- eval_batch_size: 96
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 768
- total_eval_batch_size: 384
- optimizer: Use adamw_bnb_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Bleu    |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.3935        | 0.9961 | 129  | 0.1285          | 16.5443 |
| 0.2695        | 2.0    | 259  | 0.1173          | 18.5659 |
| 0.2469        | 2.9961 | 388  | 0.1135          | 11.4429 |
| 0.2285        | 3.9846 | 516  | 0.1129          | 19.6035 |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.0.2
- Tokenizers 0.20.3