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: 0.1478
- Wer: 7.7540

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.4174        | 0.38  | 30   | 0.1791          | 7.3336 |
| 0.1753        | 0.75  | 60   | 0.1559          | 6.8509 |
| 0.136         | 1.12  | 90   | 0.1470          | 5.9946 |
| 0.0743        | 1.5   | 120  | 0.1468          | 6.3605 |
| 0.0763        | 1.88  | 150  | 0.1360          | 5.6442 |
| 0.0476        | 2.25  | 180  | 0.1487          | 6.4617 |
| 0.0332        | 2.62  | 210  | 0.1415          | 7.0689 |
| 0.0338        | 3.0   | 240  | 0.1382          | 5.4807 |
| 0.0159        | 3.38  | 270  | 0.1454          | 8.5714 |
| 0.0153        | 3.75  | 300  | 0.1427          | 5.6442 |
| 0.0124        | 4.12  | 330  | 0.1437          | 6.3605 |
| 0.0071        | 4.5   | 360  | 0.1454          | 6.0802 |
| 0.0061        | 4.88  | 390  | 0.1478          | 7.7540 |


### Framework versions

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