File size: 2,057 Bytes
cdc20a5 bcbcdd8 1685b66 7e61946 bcbcdd8 cdc20a5 bcbcdd8 cdc20a5 045fa59 cdc20a5 045fa59 cdc20a5 |
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 |
---
license: apache-2.0
language: ar
datasets:
- AymanMansour/SDN-Dialect-Dataset
- arbml/sudanese_dialect_speech
- arabic_speech_corpus
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: openai/whisper-small
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: SDN-Dialect-Dataset
type: AymanMansour/SDN-Dialect-Dataset
args: 'config: hi, split: test'
metrics:
- name: Wer
type: wer
value: 56.3216
---
<!-- 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. -->
# openai/whisper-small
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5091
- Wer: 56.3216
## 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: 32
- 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: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0157 | 13.0 | 1000 | 1.1631 | 65.9101 |
| 0.0025 | 26.0 | 2000 | 1.3416 | 58.5066 |
| 0.0009 | 39.01 | 3000 | 1.4238 | 56.6398 |
| 0.0004 | 52.01 | 4000 | 1.4800 | 56.3004 |
| 0.0002 | 65.01 | 5000 | 1.5091 | 56.3216 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|