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---
language:
- ar
license: apache-2.0
base_model: nadsoft/hamsa-v0.1-beta
tags:
- generated_from_trainer
datasets:
- nadsoft/arabic-98
metrics:
- wer
model-index:
- name: hamsa-beta-v0.3Q
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: nadsoft/arabic-98
type: nadsoft/arabic-98
metrics:
- name: Wer
type: wer
value: 19.302853050017905
---
<!-- 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. -->
# hamsa-beta-v0.3Q
This model is a fine-tuned version of [nadsoft/hamsa-v0.1-beta](https://huggingface.co/nadsoft/hamsa-v0.1-beta) on the nadsoft/arabic-98 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2362
- Wer Ortho: 21.12
- Wer: 19.3029
## 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
- 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 Ortho | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.2617 | 0.25 | 1000 | 0.2684 | 22.16 | 18.8134 |
| 0.227 | 0.5 | 2000 | 0.2565 | 18.6971 | 16.7482 |
| 0.2585 | 0.75 | 3000 | 0.2442 | 18.2400 | 16.3304 |
| 0.2632 | 1.0 | 4000 | 0.2362 | 21.12 | 19.3029 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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