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---
base_model: masoudmzb/wav2vec2-xlsr-multilingual-53-fa
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-persian-asr-shemo_lnxdx
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-persian-asr-shemo_lnxdx
This model is a fine-tuned version of [masoudmzb/wav2vec2-xlsr-multilingual-53-fa](https://huggingface.co/masoudmzb/wav2vec2-xlsr-multilingual-53-fa) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7064
- Wer: 0.3344
## 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: 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
- training_steps: 2000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.9455 | 0.62 | 100 | 1.4247 | 0.4831 |
| 1.4824 | 1.25 | 200 | 1.1107 | 0.4331 |
| 1.2516 | 1.88 | 300 | 0.9141 | 0.4136 |
| 1.0859 | 2.5 | 400 | 0.8360 | 0.3975 |
| 1.0357 | 3.12 | 500 | 0.8097 | 0.3814 |
| 1.0472 | 3.75 | 600 | 0.7550 | 0.3753 |
| 0.9963 | 4.38 | 700 | 0.7533 | 0.3636 |
| 0.9767 | 5.0 | 800 | 0.7424 | 0.3589 |
| 0.9667 | 5.62 | 900 | 0.7360 | 0.3516 |
| 0.9385 | 6.25 | 1000 | 0.7355 | 0.3487 |
| 0.9805 | 6.88 | 1100 | 0.7237 | 0.3464 |
| 0.976 | 7.5 | 1200 | 0.7078 | 0.3455 |
| 0.88 | 8.12 | 1300 | 0.7229 | 0.3438 |
| 0.9421 | 8.75 | 1400 | 0.7180 | 0.3432 |
| 0.9584 | 9.38 | 1500 | 0.7059 | 0.3364 |
| 0.88 | 10.0 | 1600 | 0.7106 | 0.3364 |
| 0.9113 | 10.62 | 1700 | 0.7125 | 0.3344 |
| 0.912 | 11.25 | 1800 | 0.7091 | 0.3353 |
| 0.9607 | 11.88 | 1900 | 0.7066 | 0.3344 |
| 0.8974 | 12.5 | 2000 | 0.7064 | 0.3344 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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