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---
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: de+es+fr+nl
metrics:
- type: wer
value: 0.38886263390044107
name: Wer
---
<!-- 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. -->
# 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: 0.3381
- Wer: 0.3889
## 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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- 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 | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.3436 | 0.36 | 200 | 1.8791 | 0.8871 |
| 1.1682 | 0.71 | 400 | 1.0307 | 0.5048 |
| 0.7321 | 1.07 | 600 | 0.6300 | 0.3665 |
| 0.4564 | 1.43 | 800 | 0.4381 | 0.3515 |
| 0.4095 | 1.79 | 1000 | 0.4027 | 0.3330 |
| 0.3813 | 2.14 | 1200 | 0.3847 | 0.3360 |
| 0.3667 | 2.5 | 1400 | 0.3734 | 0.3392 |
| 0.3583 | 2.86 | 1600 | 0.3649 | 0.3490 |
| 0.3454 | 3.22 | 1800 | 0.3588 | 0.3572 |
| 0.3422 | 3.57 | 2000 | 0.3537 | 0.3705 |
| 0.3371 | 3.93 | 2200 | 0.3503 | 0.3811 |
| 0.3291 | 4.29 | 2400 | 0.3475 | 0.3678 |
| 0.324 | 4.65 | 2600 | 0.3451 | 0.3670 |
| 0.3262 | 5.0 | 2800 | 0.3431 | 0.3710 |
| 0.3168 | 5.36 | 3000 | 0.3419 | 0.3847 |
| 0.3178 | 5.72 | 3200 | 0.3406 | 0.3833 |
| 0.3136 | 6.08 | 3400 | 0.3400 | 0.3853 |
| 0.3092 | 6.43 | 3600 | 0.3393 | 0.3896 |
| 0.3106 | 6.79 | 3800 | 0.3389 | 0.3900 |
| 0.3057 | 7.15 | 4000 | 0.3388 | 0.3803 |
| 0.3087 | 7.51 | 4200 | 0.3383 | 0.3941 |
| 0.308 | 7.86 | 4400 | 0.3382 | 0.3874 |
| 0.3036 | 8.22 | 4600 | 0.3381 | 0.3896 |
| 0.3087 | 8.58 | 4800 | 0.3380 | 0.3910 |
| 0.3079 | 8.94 | 5000 | 0.3381 | 0.3889 |
### Framework versions
- PEFT 0.7.1.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
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