File size: 3,038 Bytes
aa54b78 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 |
---
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- data/copas
metrics:
- wer
model-index:
- name: Whisper Small dysarthric Dutch
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: data/copas copas-full
type: data/copas
config: copas-full
split: test
args: copas-full
metrics:
- name: Wer
type: wer
value: 22.87060529177238
---
<!-- 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 Small dysarthric Dutch
This model is a fine-tuned version of [qmeeus/whisper-small-nl](https://huggingface.co/qmeeus/whisper-small-nl) on the data/copas copas-full dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4891
- Wer: 22.8706
## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.1493 | 2.02 | 500 | 0.3960 | 28.9779 |
| 0.0383 | 5.02 | 1000 | 0.4041 | 26.5132 |
| 0.0264 | 8.01 | 1500 | 0.4274 | 25.5890 |
| 0.0155 | 11.01 | 2000 | 0.4437 | 24.7735 |
| 0.0041 | 14.01 | 2500 | 0.4454 | 25.0453 |
| 0.0044 | 17.01 | 3000 | 0.4444 | 23.9761 |
| 0.0044 | 20.01 | 3500 | 0.4394 | 23.4868 |
| 0.0022 | 23.01 | 4000 | 0.4415 | 22.8525 |
| 0.0034 | 26.01 | 4500 | 0.4602 | 23.6499 |
| 0.0027 | 29.01 | 5000 | 0.4577 | 23.3780 |
| 0.0072 | 32.01 | 5500 | 0.4573 | 23.3962 |
| 0.0002 | 35.01 | 6000 | 0.4673 | 23.1062 |
| 0.0001 | 38.01 | 6500 | 0.4723 | 22.9975 |
| 0.0001 | 41.01 | 7000 | 0.4770 | 23.0881 |
| 0.0 | 44.01 | 7500 | 0.4807 | 23.0518 |
| 0.0 | 47.01 | 8000 | 0.4835 | 22.9612 |
| 0.0 | 50.01 | 8500 | 0.4857 | 22.9250 |
| 0.0 | 53.0 | 9000 | 0.4874 | 22.9069 |
| 0.0 | 56.0 | 9500 | 0.4887 | 22.9069 |
| 0.0 | 59.0 | 10000 | 0.4891 | 22.8706 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1
|