---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: speech-synth-large-finetune
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/neuronbit-tech/finetune_speech_synth_imperative_train/runs/8cz6mjjm)
# speech-synth-large-finetune

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4259
- Wer: 16.8396

## 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: 2
- total_train_batch_size: 16
- 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.1313        | 0.7800  | 250  | 0.4953          | 30.7145 |
| 0.0531        | 1.5585  | 500  | 0.4647          | 28.1055 |
| 0.0269        | 2.3370  | 750  | 0.4448          | 19.9526 |
| 0.0101        | 3.1154  | 1000 | 0.4392          | 23.0062 |
| 0.0064        | 3.8955  | 1250 | 0.4053          | 22.2947 |
| 0.0057        | 4.6739  | 1500 | 0.4148          | 19.3003 |
| 0.0044        | 5.4524  | 1750 | 0.4028          | 17.9958 |
| 0.0047        | 6.2309  | 2000 | 0.4125          | 19.0631 |
| 0.003         | 7.0094  | 2250 | 0.3979          | 17.7883 |
| 0.0038        | 7.7894  | 2500 | 0.3923          | 20.5455 |
| 0.0           | 8.5679  | 2750 | 0.4077          | 17.6401 |
| 0.0002        | 9.3463  | 3000 | 0.4050          | 17.3733 |
| 0.0009        | 10.1248 | 3250 | 0.4101          | 17.0471 |
| 0.0005        | 10.9048 | 3500 | 0.4227          | 17.1954 |
| 0.0           | 11.6833 | 3750 | 0.4217          | 17.2250 |
| 0.0002        | 12.4618 | 4000 | 0.4241          | 17.0471 |
| 0.0           | 13.2402 | 4250 | 0.4239          | 16.9582 |
| 0.0005        | 14.0187 | 4500 | 0.4250          | 16.6617 |
| 0.0           | 14.7988 | 4750 | 0.4254          | 16.8396 |
| 0.0001        | 15.5772 | 5000 | 0.4259          | 16.8396 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0