---
language:
- en
license: mit
base_model: distil-whisper/distil-small.en
tags:
- generated_from_trainer
datasets:
- atc
metrics:
- wer
model-index:
- name: Whisper Large v3 1500 Epochs 2 - nullonesix
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: atc
      type: atc
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 39.23487544483986
---

<!-- 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 Large v3 1500 Epochs 2 - nullonesix

This model is a fine-tuned version of [distil-whisper/distil-small.en](https://huggingface.co/distil-whisper/distil-small.en) on the atc dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4151
- Wer: 39.2349

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 2.8313        | 3.5714  | 100  | 2.7177          | 74.1548 |
| 1.1366        | 7.1429  | 200  | 1.6407          | 63.0338 |
| 0.4394        | 10.7143 | 300  | 1.4737          | 47.4644 |
| 0.1686        | 14.2857 | 400  | 1.4481          | 46.3968 |
| 0.0761        | 17.8571 | 500  | 1.3707          | 40.8808 |
| 0.0452        | 21.4286 | 600  | 1.4051          | 38.5231 |
| 0.0188        | 25.0    | 700  | 1.4044          | 36.7883 |
| 0.0167        | 28.5714 | 800  | 1.4217          | 38.8345 |
| 0.0084        | 32.1429 | 900  | 1.4120          | 48.5765 |
| 0.0033        | 35.7143 | 1000 | 1.4151          | 39.2349 |
| 0.0022        | 39.2857 | 1100 | 1.4401          | 39.7242 |
| 0.0008        | 42.8571 | 1200 | 1.4591          | 39.5907 |
| 0.0007        | 46.4286 | 1300 | 1.4679          | 39.5907 |
| 0.0006        | 50.0    | 1400 | 1.4724          | 39.8577 |
| 0.0007        | 53.5714 | 1500 | 1.4737          | 39.7242 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1