metadata
language:
- fy
base_model: distil-small.en
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_6_1
metrics:
- wer
model-index:
- name: DistilFT-Frisian-10h
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_6_fy_NL
type: mozilla-foundation/common_voice_6_1
args: 'config: fy-NL, split: train-10h'
metrics:
- name: Wer
type: wer
value: 35.804669399394044
DistilFT-Frisian-10h
This model is a fine-tuned version of distil-small.en on the mozilla-foundation/common_voice_6_fy_NL dataset. It achieves the following results on the evaluation set:
- Loss: 0.6854
- Wer: 35.8047
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: 8
- 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: 300
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.0989 | 0.5348 | 500 | 1.2112 | 59.2408 |
| 0.5734 | 1.0695 | 1000 | 0.8419 | 46.6405 |
| 0.4798 | 1.6043 | 1500 | 0.7341 | 42.1137 |
| 0.2483 | 2.1390 | 2000 | 0.6788 | 39.4190 |
| 0.2367 | 2.6738 | 2500 | 0.6554 | 37.7865 |
| 0.1197 | 3.2086 | 3000 | 0.6613 | 36.7706 |
| 0.0969 | 3.7433 | 3500 | 0.6591 | 36.7279 |
| 0.0468 | 4.2781 | 4000 | 0.6777 | 35.8688 |
| 0.0358 | 4.8128 | 4500 | 0.6771 | 35.7583 |
| 0.028 | 5.3476 | 5000 | 0.6854 | 35.8047 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1