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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: mounir4
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. -->
# mounir4
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6829
- Wer: 1
## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:---:|
| 3.3494 | 8.51 | 500 | 3.1482 | 1 |
| 2.9331 | 17.02 | 1000 | 2.9053 | 1 |
| 2.8691 | 25.53 | 1500 | 2.8793 | 1 |
| 2.8393 | 34.04 | 2000 | 2.8696 | 1 |
| 1.9588 | 42.55 | 2500 | 1.5982 | 1 |
| 0.9108 | 51.06 | 3000 | 0.8335 | 1 |
| 0.7196 | 59.57 | 3500 | 0.7443 | 1 |
| 0.6198 | 68.09 | 4000 | 0.6949 | 1 |
| 0.5558 | 76.6 | 4500 | 0.6862 | 1 |
| 0.5152 | 85.11 | 5000 | 0.6743 | 1 |
| 0.4781 | 93.62 | 5500 | 0.6668 | 1 |
| 0.4442 | 102.13 | 6000 | 0.6587 | 1 |
| 0.4255 | 110.64 | 6500 | 0.6498 | 1 |
| 0.408 | 119.15 | 7000 | 0.6698 | 1 |
| 0.3888 | 127.66 | 7500 | 0.6739 | 1 |
| 0.3815 | 136.17 | 8000 | 0.6754 | 1 |
| 0.3704 | 144.68 | 8500 | 0.6843 | 1 |
| 0.3625 | 153.19 | 9000 | 0.6707 | 1 |
| 0.356 | 161.7 | 9500 | 0.6812 | 1 |
| 0.3541 | 170.21 | 10000 | 0.6829 | 1 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
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