---
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v2-custom-hi
  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-large-v2-custom-hi

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3389
- Wer: 0.2186

## 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: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 5000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0523        | 2.44  | 500  | 0.2123          | 0.2664 |
| 0.0187        | 4.89  | 1000 | 0.2237          | 0.2370 |
| 0.0041        | 7.33  | 1500 | 0.2647          | 0.2310 |
| 0.0028        | 9.78  | 2000 | 0.2904          | 0.2344 |
| 0.0015        | 12.22 | 2500 | 0.2908          | 0.2268 |
| 0.0003        | 14.67 | 3000 | 0.3022          | 0.2197 |
| 0.0003        | 17.11 | 3500 | 0.3249          | 0.2195 |
| 0.0003        | 19.56 | 4000 | 0.3217          | 0.2161 |
| 0.0           | 22.0  | 4500 | 0.3335          | 0.2181 |
| 0.0           | 24.45 | 5000 | 0.3389          | 0.2186 |


### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3