transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer nl base_model:openai/whisper-large-v2 license:apache-2.0 endpoints_compatible region:us
---
language:
- nl
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Large 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 Large V2

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: 0.2110
- Wer: 7.8855

## 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: 3e-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: 20
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5451        | 0.49  | 30   | 0.2331          | 9.3771  |
| 0.299         | 0.98  | 60   | 0.1932          | 11.1867 |
| 0.1459        | 1.48  | 90   | 0.1867          | 11.2415 |
| 0.1368        | 1.97  | 120  | 0.1862          | 10.0022 |
| 0.0654        | 2.46  | 150  | 0.1957          | 13.2156 |
| 0.0592        | 2.95  | 180  | 0.1975          | 9.3222  |
| 0.031         | 3.44  | 210  | 0.2102          | 8.1377  |
| 0.0226        | 3.93  | 240  | 0.1986          | 7.8965  |
| 0.0119        | 4.43  | 270  | 0.2104          | 8.0061  |
| 0.0094        | 4.92  | 300  | 0.2110          | 7.8855  |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0
