---
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