---
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: dgx2_whisper_small_mozilla_noisy_distil_epochs_50_batch_8
  results: []
---

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# dgx2_whisper_small_mozilla_noisy_distil_epochs_50_batch_8

This model is a fine-tuned version of [rohitp1/kkkh_whisper_small_distillation_att_loss_mozilla_epochs_100_batch_4_concat_dataset](https://huggingface.co/rohitp1/kkkh_whisper_small_distillation_att_loss_mozilla_epochs_100_batch_4_concat_dataset) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1254
- Wer: 20.5209

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 256
- total_train_batch_size: 2048
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0006        | 4.39  | 150  | 0.5538          | 19.3893 |
| 0.1453        | 8.78  | 300  | 0.7751          | 20.7263 |
| 0.3233        | 13.17 | 450  | 0.8857          | 20.7994 |
| 0.486         | 17.55 | 600  | 1.0980          | 20.6462 |
| 0.6433        | 21.94 | 750  | 1.1264          | 20.5835 |
| 0.6452        | 26.33 | 900  | 1.1254          | 20.5209 |


### Framework versions

- Transformers 4.28.1
- Pytorch 1.12.1
- Datasets 2.8.0
- Tokenizers 0.13.2