---
base_model: ad019el/Kabyle_xlsr-finetuned-tamasheq.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Kabyle_xlsr-finetuned-tamasheq.en
  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. -->

# Kabyle_xlsr-finetuned-tamasheq.en

This model is a fine-tuned version of [ad019el/Kabyle_xlsr-finetuned-tamasheq.en](https://huggingface.co/ad019el/Kabyle_xlsr-finetuned-tamasheq.en) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3502
- Wer: 0.8867

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 200

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 6.9014        | 3.41  | 300  | 2.9702          | 1.0    |
| 2.922         | 6.82  | 600  | 2.7233          | 1.0    |
| 2.4143        | 10.23 | 900  | 1.3795          | 0.9122 |
| 1.6795        | 13.64 | 1200 | 1.3346          | 0.8810 |
| 1.5           | 17.05 | 1500 | 1.3412          | 0.9207 |
| 1.4151        | 20.45 | 1800 | 1.3307          | 0.9037 |
| 1.3298        | 23.86 | 2100 | 1.3467          | 0.8782 |
| 1.2517        | 27.27 | 2400 | 1.3027          | 0.8768 |
| 1.2162        | 30.68 | 2700 | 1.3134          | 0.8810 |
| 1.1987        | 34.09 | 3000 | 1.3336          | 0.8754 |
| 1.1706        | 37.5  | 3300 | 1.3502          | 0.8867 |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3