peft safetensors whisper generated_from_trainer dataset:facebook/voxpopuli base_model:openai/whisper-small license:apache-2.0 model-index region:us
---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: openai/whisper-small
datasets:
- facebook/voxpopuli
metrics:
- wer
model-index:
- name: WhisperForSpokenNER-end2end
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: facebook/voxpopuli de+es+fr+nl
      type: facebook/voxpopuli
      split: None
    metrics:
    - type: wer
      value: 0.1421388512860182
      name: Wer
---

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# WhisperForSpokenNER-end2end

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the facebook/voxpopuli de+es+fr+nl dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3440
- Combined Wer: 0.2231
- F1 Score: 0.5368
- Label F1: 0.6908
- Wer: 0.1421

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Combined Wer | F1 Score | Label F1 | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:--------:|:--------:|:------:|
| 1.1583        | 0.1   | 500  | 1.0361          | 0.3217       | 0.0746   | 0.1415   | 0.2067 |
| 0.4069        | 0.2   | 1000 | 0.4111          | 0.2203       | 0.4223   | 0.5940   | 0.1235 |
| 0.3708        | 0.3   | 1500 | 0.3768          | 0.2201       | 0.4609   | 0.6267   | 0.1295 |
| 0.3512        | 0.4   | 2000 | 0.3624          | 0.2223       | 0.5142   | 0.6835   | 0.1359 |
| 0.3411        | 0.5   | 2500 | 0.3543          | 0.2204       | 0.5225   | 0.6883   | 0.1374 |
| 0.3313        | 1.02  | 3000 | 0.3492          | 0.2235       | 0.5193   | 0.6808   | 0.1398 |
| 0.3252        | 1.12  | 3500 | 0.3459          | 0.2251       | 0.5333   | 0.6893   | 0.1436 |
| 0.3293        | 1.22  | 4000 | 0.3447          | 0.2237       | 0.5325   | 0.6860   | 0.1416 |
| 0.321         | 1.32  | 4500 | 0.3443          | 0.2238       | 0.5366   | 0.6905   | 0.1425 |
| 0.3223        | 1.42  | 5000 | 0.3440          | 0.2231       | 0.5368   | 0.6908   | 0.1421 |


### Framework versions

- PEFT 0.7.1.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1