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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_partial
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_partial
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: 0.8069
- Wer: 0.3490
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.3226 | 0.62 | 100 | 1.4548 | 0.4851 |
| 1.7166 | 1.25 | 200 | 1.2460 | 0.4279 |
| 1.4987 | 1.88 | 300 | 1.0671 | 0.4194 |
| 1.3771 | 2.5 | 400 | 0.9784 | 0.4054 |
| 1.3217 | 3.12 | 500 | 0.9450 | 0.3905 |
| 1.3272 | 3.75 | 600 | 0.8851 | 0.3841 |
| 1.3025 | 4.38 | 700 | 0.8748 | 0.3779 |
| 1.2719 | 5.0 | 800 | 0.8674 | 0.3724 |
| 1.2563 | 5.62 | 900 | 0.8467 | 0.3692 |
| 1.2451 | 6.25 | 1000 | 0.8440 | 0.3645 |
| 1.2585 | 6.88 | 1100 | 0.8292 | 0.3610 |
| 1.2633 | 7.5 | 1200 | 0.8137 | 0.3601 |
| 1.1923 | 8.12 | 1300 | 0.8263 | 0.3575 |
| 1.2349 | 8.75 | 1400 | 0.8184 | 0.3551 |
| 1.2511 | 9.38 | 1500 | 0.8078 | 0.3516 |
| 1.1779 | 10.0 | 1600 | 0.8102 | 0.3505 |
| 1.2161 | 10.62 | 1700 | 0.8123 | 0.3499 |
| 1.1967 | 11.25 | 1800 | 0.8086 | 0.3502 |
| 1.2454 | 11.88 | 1900 | 0.8066 | 0.3490 |
| 1.1928 | 12.5 | 2000 | 0.8069 | 0.3490 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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