---
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo-whisper-lg-3-Nov3
  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. -->

# torgo-whisper-lg-3-Nov3

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: 0.0877
- Wer: 5.6146

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 1.2844        | 0.3190  | 100  | 0.3944          | 28.6798 |
| 0.2992        | 0.6380  | 200  | 0.2182          | 17.4507 |
| 0.197         | 0.9569  | 300  | 0.1986          | 13.6571 |
| 0.1299        | 1.2759  | 400  | 0.1599          | 12.5190 |
| 0.1001        | 1.5949  | 500  | 0.1700          | 12.2155 |
| 0.1038        | 1.9139  | 600  | 0.1407          | 9.1806  |
| 0.0728        | 2.2329  | 700  | 0.1351          | 9.6358  |
| 0.0652        | 2.5518  | 800  | 0.1090          | 7.9666  |
| 0.0529        | 2.8708  | 900  | 0.1168          | 8.1942  |
| 0.0338        | 3.1898  | 1000 | 0.1132          | 6.8285  |
| 0.0358        | 3.5088  | 1100 | 0.0980          | 6.9044  |
| 0.0381        | 3.8278  | 1200 | 0.0820          | 6.7527  |
| 0.0245        | 4.1467  | 1300 | 0.0862          | 5.2352  |
| 0.0299        | 4.4657  | 1400 | 0.1068          | 5.9181  |
| 0.0261        | 4.7847  | 1500 | 0.0937          | 6.4492  |
| 0.0205        | 5.1037  | 1600 | 0.1019          | 7.2838  |
| 0.017         | 5.4226  | 1700 | 0.0990          | 5.6904  |
| 0.0115        | 5.7416  | 1800 | 0.0842          | 5.6146  |
| 0.018         | 6.0606  | 1900 | 0.1041          | 5.6904  |
| 0.0112        | 6.3796  | 2000 | 0.1135          | 7.1320  |
| 0.0174        | 6.6986  | 2100 | 0.0939          | 5.0835  |
| 0.0117        | 7.0175  | 2200 | 0.1092          | 5.9181  |
| 0.0121        | 7.3365  | 2300 | 0.0931          | 5.4628  |
| 0.0075        | 7.6555  | 2400 | 0.0974          | 5.6146  |
| 0.013         | 7.9745  | 2500 | 0.1142          | 5.7663  |
| 0.0063        | 8.2935  | 2600 | 0.1108          | 6.1457  |
| 0.0122        | 8.6124  | 2700 | 0.0929          | 5.6146  |
| 0.0125        | 8.9314  | 2800 | 0.0905          | 5.6146  |
| 0.0132        | 9.2504  | 2900 | 0.1202          | 6.1457  |
| 0.0132        | 9.5694  | 3000 | 0.0925          | 5.0835  |
| 0.0087        | 9.8884  | 3100 | 0.1028          | 5.0835  |
| 0.0043        | 10.2073 | 3200 | 0.0997          | 5.6146  |
| 0.004         | 10.5263 | 3300 | 0.0955          | 5.0835  |
| 0.007         | 10.8453 | 3400 | 0.0915          | 5.1593  |
| 0.0072        | 11.1643 | 3500 | 0.0814          | 5.3869  |
| 0.0069        | 11.4833 | 3600 | 0.0887          | 4.7800  |
| 0.0082        | 11.8022 | 3700 | 0.0940          | 5.6904  |
| 0.0105        | 12.1212 | 3800 | 0.0936          | 5.2352  |
| 0.0039        | 12.4402 | 3900 | 0.0966          | 5.3869  |
| 0.002         | 12.7592 | 4000 | 0.0820          | 4.7800  |
| 0.0032        | 13.0781 | 4100 | 0.0916          | 5.0835  |
| 0.0009        | 13.3971 | 4200 | 0.0877          | 5.6146  |


### Framework versions

- Transformers 4.43.4
- Pytorch 2.4.1
- Datasets 3.0.0
- Tokenizers 0.19.1