---
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