File size: 2,063 Bytes
5b9449a ad29419 5b9449a ad29419 5b9449a ad29419 5b9449a ad29419 5b9449a ad29419 5b9449a ad29419 5b9449a ad29419 5b9449a ad29419 5b9449a ad29419 5b9449a |
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 |
---
language:
- yo
license: apache-2.0
base_model: DereAbdulhameed/new_whisper_yoruba
tags:
- whisper-event
- generated_from_trainer
datasets:
- OpenSLR
metrics:
- wer
model-index:
- name: Whisper Small Yoruba - Dere Abdulhameed
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 16.1 & SLR86
type: OpenSLR
config: yo
split: None
args: yo
metrics:
- name: Wer
type: wer
value: 33.08135740700457
---
<!-- 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 Yoruba - Dere Abdulhameed
This model is a fine-tuned version of [DereAbdulhameed/new_whisper_yoruba](https://huggingface.co/DereAbdulhameed/new_whisper_yoruba) on the Common Voice 16.1 & SLR86 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7726
- Wer: 33.0814
## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0001 | 17.01 | 1000 | 1.6166 | 33.3043 |
| 0.0001 | 35.01 | 2000 | 1.7029 | 32.9563 |
| 0.0 | 53.01 | 3000 | 1.7515 | 33.0868 |
| 0.0 | 71.01 | 4000 | 1.7726 | 33.0814 |
### Framework versions
- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|