---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-finetune-XLSR_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-finetune-XLSR_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: 0.2804
- Wer: 0.3265

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.9859        | 0.83  | 400   | 2.0919          | 0.9982 |
| 0.8639        | 1.66  | 800   | 0.4365          | 0.5925 |
| 0.4879        | 2.49  | 1200  | 0.3467          | 0.5079 |
| 0.3732        | 3.32  | 1600  | 0.3267          | 0.4756 |
| 0.314         | 4.15  | 2000  | 0.2835          | 0.4314 |
| 0.274         | 4.97  | 2400  | 0.2915          | 0.4364 |
| 0.2463        | 5.8   | 2800  | 0.3050          | 0.4277 |
| 0.2354        | 6.63  | 3200  | 0.2766          | 0.4179 |
| 0.2101        | 7.46  | 3600  | 0.2896          | 0.4071 |
| 0.1976        | 8.29  | 4000  | 0.2856          | 0.4099 |
| 0.186         | 9.12  | 4400  | 0.2849          | 0.3987 |
| 0.1758        | 9.95  | 4800  | 0.2819          | 0.4026 |
| 0.1667        | 10.78 | 5200  | 0.2869          | 0.3934 |
| 0.1508        | 11.61 | 5600  | 0.2793          | 0.3851 |
| 0.1468        | 12.44 | 6000  | 0.2777          | 0.3836 |
| 0.1322        | 13.26 | 6400  | 0.2731          | 0.3767 |
| 0.1295        | 14.09 | 6800  | 0.2833          | 0.3741 |
| 0.1157        | 14.92 | 7200  | 0.2815          | 0.3786 |
| 0.1147        | 15.75 | 7600  | 0.2684          | 0.3741 |
| 0.1099        | 16.58 | 8000  | 0.2704          | 0.3677 |
| 0.1056        | 17.41 | 8400  | 0.2744          | 0.3668 |
| 0.0983        | 18.24 | 8800  | 0.2675          | 0.3676 |
| 0.0975        | 19.07 | 9200  | 0.2787          | 0.3588 |
| 0.0906        | 19.9  | 9600  | 0.2749          | 0.3537 |
| 0.0862        | 20.73 | 10000 | 0.2875          | 0.3557 |
| 0.0812        | 21.55 | 10400 | 0.2863          | 0.3482 |
| 0.0761        | 22.38 | 10800 | 0.2739          | 0.3513 |
| 0.0738        | 23.21 | 11200 | 0.2878          | 0.3467 |
| 0.0678        | 24.04 | 11600 | 0.2886          | 0.3399 |
| 0.0661        | 24.87 | 12000 | 0.2958          | 0.3380 |
| 0.0623        | 25.7  | 12400 | 0.2779          | 0.3354 |
| 0.0586        | 26.53 | 12800 | 0.2871          | 0.3333 |
| 0.0563        | 27.36 | 13200 | 0.2895          | 0.3316 |
| 0.0554        | 28.19 | 13600 | 0.2846          | 0.3277 |
| 0.0522        | 29.02 | 14000 | 0.2752          | 0.3276 |
| 0.0498        | 29.84 | 14400 | 0.2804          | 0.3265 |


### Framework versions

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