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---
license: apache-2.0
base_model: boumehdi/wav2vec2-large-xlsr-moroccan-darija
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-moroccan-darija-v2
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-large-xlsr-moroccan-darija-v2
This model is a fine-tuned version of [boumehdi/wav2vec2-large-xlsr-moroccan-darija](https://huggingface.co/boumehdi/wav2vec2-large-xlsr-moroccan-darija) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2106
- Wer: 0.1908
## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 4.8709 | 0.5359 | 500 | 0.4977 | 0.4531 |
| 0.4841 | 1.0718 | 1000 | 0.2715 | 0.2724 |
| 0.3611 | 1.6077 | 1500 | 0.2311 | 0.2441 |
| 0.3088 | 2.1436 | 2000 | 0.2042 | 0.2366 |
| 0.2666 | 2.6795 | 2500 | 0.1999 | 0.2352 |
| 0.2303 | 3.2154 | 3000 | 0.1900 | 0.2231 |
| 0.1921 | 3.7513 | 3500 | 0.1839 | 0.2195 |
| 0.1629 | 4.2872 | 4000 | 0.1783 | 0.2153 |
| 0.1403 | 4.8232 | 4500 | 0.1904 | 0.2041 |
| 0.1178 | 5.3591 | 5000 | 0.1739 | 0.2118 |
| 0.1124 | 5.8950 | 5500 | 0.1996 | 0.1970 |
| 0.0981 | 6.4309 | 6000 | 0.1890 | 0.2016 |
| 0.091 | 6.9668 | 6500 | 0.2020 | 0.1949 |
| 0.077 | 7.5027 | 7000 | 0.2057 | 0.1929 |
| 0.0769 | 8.0386 | 7500 | 0.2093 | 0.1935 |
| 0.0726 | 8.5745 | 8000 | 0.2097 | 0.1924 |
| 0.0685 | 9.1104 | 8500 | 0.2088 | 0.1913 |
| 0.0625 | 9.6463 | 9000 | 0.2106 | 0.1908 |
### Framework versions
- Transformers 4.43.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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