---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2_XLSR_darija_maroc
  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. -->

# wav2vec2_XLSR_darija_maroc

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2740
- Wer: 0.3247

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.9874        | 0.83  | 400   | 2.4916          | 0.9978 |
| 0.9314        | 1.66  | 800   | 0.4379          | 0.5839 |
| 0.4856        | 2.49  | 1200  | 0.3485          | 0.5001 |
| 0.3859        | 3.32  | 1600  | 0.3331          | 0.4768 |
| 0.3271        | 4.15  | 2000  | 0.2932          | 0.4369 |
| 0.2842        | 4.97  | 2400  | 0.2988          | 0.4422 |
| 0.2482        | 5.8   | 2800  | 0.2815          | 0.4174 |
| 0.2252        | 6.63  | 3200  | 0.2967          | 0.4316 |
| 0.2115        | 7.46  | 3600  | 0.2719          | 0.4007 |
| 0.1965        | 8.29  | 4000  | 0.2867          | 0.3985 |
| 0.1823        | 9.12  | 4400  | 0.2744          | 0.4008 |
| 0.1712        | 9.95  | 4800  | 0.2589          | 0.3873 |
| 0.156         | 10.78 | 5200  | 0.2589          | 0.3745 |
| 0.1536        | 11.61 | 5600  | 0.2628          | 0.3799 |
| 0.1404        | 12.44 | 6000  | 0.2704          | 0.3805 |
| 0.1402        | 13.26 | 6400  | 0.2748          | 0.3784 |
| 0.1305        | 14.09 | 6800  | 0.2780          | 0.3769 |
| 0.121         | 14.92 | 7200  | 0.2760          | 0.3698 |
| 0.1147        | 15.75 | 7600  | 0.2723          | 0.3733 |
| 0.1076        | 16.58 | 8000  | 0.2661          | 0.3671 |
| 0.1013        | 17.41 | 8400  | 0.2709          | 0.3665 |
| 0.0964        | 18.24 | 8800  | 0.2748          | 0.3599 |
| 0.0946        | 19.07 | 9200  | 0.2696          | 0.3550 |
| 0.0916        | 19.9  | 9600  | 0.2649          | 0.3596 |
| 0.0849        | 20.73 | 10000 | 0.2905          | 0.3573 |
| 0.0803        | 21.55 | 10400 | 0.2646          | 0.3496 |
| 0.0748        | 22.38 | 10800 | 0.2871          | 0.3486 |
| 0.0739        | 23.21 | 11200 | 0.2751          | 0.3432 |
| 0.0699        | 24.04 | 11600 | 0.2857          | 0.3426 |
| 0.0637        | 24.87 | 12000 | 0.2690          | 0.3377 |
| 0.0627        | 25.7  | 12400 | 0.2737          | 0.3371 |
| 0.0601        | 26.53 | 12800 | 0.2752          | 0.3358 |
| 0.0564        | 27.36 | 13200 | 0.2827          | 0.3329 |
| 0.0536        | 28.19 | 13600 | 0.2764          | 0.3310 |
| 0.0508        | 29.02 | 14000 | 0.2750          | 0.3281 |
| 0.0495        | 29.84 | 14400 | 0.2740          | 0.3247 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1