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

# easycall-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: 0.0614
- Wer: 8.1563

## 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.4391        | 0.0946 | 100  | 0.2666          | 33.1351 |
| 0.1608        | 0.1892 | 200  | 0.1262          | 17.0773 |
| 0.1116        | 0.2838 | 300  | 0.0969          | 12.4894 |
| 0.119         | 0.3784 | 400  | 0.1043          | 13.5939 |
| 0.0981        | 0.4730 | 500  | 0.0961          | 12.3619 |
| 0.0943        | 0.5676 | 600  | 0.0968          | 11.6822 |
| 0.087         | 0.6623 | 700  | 0.0886          | 11.5548 |
| 0.086         | 0.7569 | 800  | 0.0681          | 8.7935  |
| 0.0706        | 0.8515 | 900  | 0.0718          | 9.2608  |
| 0.067         | 0.9461 | 1000 | 0.0695          | 8.7935  |
| 0.0571        | 1.0407 | 1100 | 0.0682          | 8.3263  |
| 0.0596        | 1.1353 | 1200 | 0.0683          | 9.3883  |
| 0.0445        | 1.2299 | 1300 | 0.0677          | 8.0289  |
| 0.0577        | 1.3245 | 1400 | 0.0665          | 9.4308  |
| 0.0544        | 1.4191 | 1500 | 0.0633          | 8.5387  |
| 0.0491        | 1.5137 | 1600 | 0.0671          | 9.6856  |
| 0.0536        | 1.6083 | 1700 | 0.0617          | 8.6661  |
| 0.0406        | 1.7029 | 1800 | 0.0823          | 9.0059  |
| 0.0543        | 1.7975 | 1900 | 0.0614          | 8.1563  |


### Framework versions

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