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: 0.1460
- Wer: 4.9428

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.4482        | 0.38  | 30   | 0.2117          | 7.6578 |
| 0.1832        | 0.75  | 60   | 0.1544          | 6.4124 |
| 0.1302        | 1.12  | 90   | 0.1546          | 6.0953 |
| 0.0785        | 1.5   | 120  | 0.1436          | 6.8765 |
| 0.0777        | 1.88  | 150  | 0.1350          | 5.3914 |
| 0.0546        | 2.25  | 180  | 0.1431          | 5.4069 |
| 0.0311        | 2.62  | 210  | 0.1411          | 9.5452 |
| 0.0334        | 3.0   | 240  | 0.1389          | 6.0334 |
| 0.0172        | 3.38  | 270  | 0.1404          | 5.1361 |
| 0.0147        | 3.75  | 300  | 0.1414          | 5.2754 |
| 0.0108        | 4.12  | 330  | 0.1420          | 5.0588 |
| 0.0073        | 4.5   | 360  | 0.1454          | 4.9273 |
| 0.007         | 4.88  | 390  | 0.1460          | 4.9428 |


### Framework versions

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