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: 0.1401
- Wer: 5.5491

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.4119        | 0.38  | 30   | 0.1653          | 7.8245 |
| 0.1737        | 0.75  | 60   | 0.1446          | 5.7271 |
| 0.1437        | 1.12  | 90   | 0.1420          | 6.7487 |
| 0.0785        | 1.5   | 120  | 0.1317          | 5.1931 |
| 0.0707        | 1.88  | 150  | 0.1309          | 6.2379 |
| 0.0496        | 2.25  | 180  | 0.1369          | 5.9670 |
| 0.0318        | 2.62  | 210  | 0.1316          | 6.0367 |
| 0.0341        | 3.0   | 240  | 0.1290          | 5.5568 |
| 0.0166        | 3.38  | 270  | 0.1339          | 4.9532 |
| 0.0147        | 3.75  | 300  | 0.1353          | 5.4949 |
| 0.0109        | 4.12  | 330  | 0.1365          | 5.6342 |
| 0.0072        | 4.5   | 360  | 0.1402          | 5.4640 |
| 0.0071        | 4.88  | 390  | 0.1401          | 5.5491 |


### Framework versions

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