---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-v3-raw-segments
  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-v3-raw-segments

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: 1.0487
- Wer: 38.5643

## 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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.6455        | 1.0    | 77   | 0.5327          | 38.8982 |
| 0.2879        | 2.0    | 154  | 0.5643          | 38.3139 |
| 0.1475        | 3.0    | 231  | 0.6085          | 39.4825 |
| 0.0782        | 4.0    | 308  | 0.6817          | 39.4825 |
| 0.0474        | 5.0    | 385  | 0.7397          | 39.3990 |
| 0.0278        | 6.0    | 462  | 0.8067          | 38.3139 |
| 0.018         | 7.0    | 539  | 0.8780          | 41.0684 |
| 0.0089        | 8.0    | 616  | 0.9437          | 38.9816 |
| 0.0039        | 9.0    | 693  | 1.0166          | 38.0634 |
| 0.0014        | 9.8758 | 760  | 1.0487          | 38.5643 |


### Framework versions

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