---
language:
- ar
license: apache-2.0
base_model: nadsoft/hamsa-v0.1-beta
tags:
- generated_from_trainer
datasets:
- nadsoft/nadsoft-meetings-v2
metrics:
- wer
model-index:
- name: Hamsa-meetings
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: nadsoft/nadsoft-meetings-v2
      type: nadsoft/nadsoft-meetings-v2
    metrics:
    - name: Wer
      type: wer
      value: 43.449519230769226
---

<!-- 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-meetings

This model is a fine-tuned version of [nadsoft/hamsa-v0.1-beta](https://huggingface.co/nadsoft/hamsa-v0.1-beta) on the nadsoft/nadsoft-meetings-v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9346
- Wer Ortho: 43.4495
- Wer: 43.4495

## 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: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.4883        | 2.91  | 250  | 0.6170          | 40.2644   | 40.2644 |
| 0.1678        | 5.81  | 500  | 0.6893          | 43.6899   | 43.6899 |
| 0.0749        | 8.72  | 750  | 0.7367          | 42.0673   | 42.0673 |
| 0.0352        | 11.63 | 1000 | 0.7829          | 42.6683   | 42.6683 |
| 0.0214        | 14.53 | 1250 | 0.8553          | 43.9904   | 43.9904 |
| 0.0146        | 17.44 | 1500 | 0.9061          | 43.3894   | 43.3894 |
| 0.0112        | 20.35 | 1750 | 0.9225          | 44.2909   | 44.2909 |
| 0.0104        | 23.26 | 2000 | 0.9346          | 43.4495   | 43.4495 |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0