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---
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
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