---
base_model: openai/whisper-small
library_name: transformers
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: whisper-small-hyper-tuned-v2
  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. -->

# whisper-small-hyper-tuned-v2

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2138
- Wer: 0.3859

## 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: 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: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.2719        | 0.0330 | 100  | 0.3551          | 0.5211 |
| 0.2793        | 0.0660 | 200  | 0.3262          | 0.4921 |
| 0.2831        | 0.0990 | 300  | 0.3306          | 0.4927 |
| 0.2775        | 0.1320 | 400  | 0.3631          | 0.5363 |
| 0.2849        | 0.1650 | 500  | 0.3488          | 0.5040 |
| 0.2692        | 0.1980 | 600  | 0.3202          | 0.4967 |
| 0.2528        | 0.2309 | 700  | 0.2838          | 0.4400 |
| 0.2155        | 0.2639 | 800  | 0.2489          | 0.4116 |
| 0.1929        | 0.2969 | 900  | 0.2220          | 0.3912 |
| 0.1709        | 0.3299 | 1000 | 0.2138          | 0.3859 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.1.0+cu118
- Datasets 3.0.1
- Tokenizers 0.20.0