---
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
model-index:
- name: Muaalem-model-dev
  results: []
---

<!-- 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. -->

# Muaalem-model-dev

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0212
- Per Phonemes: 0.0058
- Per Hams Or Jahr: 0.0026
- Per Shidda Or Rakhawa: 0.0040
- Per Tafkheem Or Taqeeq: 0.0030
- Per Itbaq: 0.0019
- Per Safeer: 0.0022
- Per Qalqla: 0.0020
- Per Tikraar: 0.0023
- Per Tafashie: 0.0160
- Per Istitala: 0.0019
- Per Ghonna: 0.0027
- Average Per: 0.0040

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 90
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Per Phonemes | Per Hams Or Jahr | Per Shidda Or Rakhawa | Per Tafkheem Or Taqeeq | Per Itbaq | Per Safeer | Per Qalqla | Per Tikraar | Per Tafashie | Per Istitala | Per Ghonna | Average Per |
|:-------------:|:------:|:----:|:---------------:|:------------:|:----------------:|:---------------------:|:----------------------:|:---------:|:----------:|:----------:|:-----------:|:------------:|:------------:|:----------:|:-----------:|
| 0.8303        | 0.2022 | 73   | 0.1027          | 0.0612       | 0.0229           | 0.0245                | 0.1080                 | 0.0327    | 0.0658     | 0.0270     | 0.0433      | 0.2467       | 0.0236       | 0.0243     | 0.0618      |
| 0.0593        | 0.4044 | 146  | 0.0451          | 0.0207       | 0.0041           | 0.0055                | 0.0066                 | 0.0032    | 0.0042     | 0.0042     | 0.0032      | 0.0566       | 0.0029       | 0.0038     | 0.0105      |
| 0.0434        | 0.6066 | 219  | 0.0306          | 0.0081       | 0.0031           | 0.0043                | 0.0032                 | 0.0021    | 0.0025     | 0.0026     | 0.0028      | 0.0322       | 0.0024       | 0.0034     | 0.0061      |
| 0.032         | 0.8089 | 292  | 0.0212          | 0.0058       | 0.0026           | 0.0040                | 0.0030                 | 0.0019    | 0.0022     | 0.0020     | 0.0023      | 0.0160       | 0.0019       | 0.0027     | 0.0040      |


### Framework versions

- Transformers 4.55.0
- Pytorch 2.8.0+cu128
- Datasets 3.3.2
- Tokenizers 0.21.4