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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-burak-new-300-v2-3
  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-burak-new-300-v2-3

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2910
- Wer: 0.2712

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 71

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 7.5554        | 4.9   | 500  | 3.1912          | 1.0    |
| 3.1116        | 9.8   | 1000 | 2.5931          | 1.0    |
| 1.291         | 14.71 | 1500 | 0.4394          | 0.5575 |
| 0.6214        | 19.61 | 2000 | 0.3243          | 0.4370 |
| 0.4501        | 24.51 | 2500 | 0.2890          | 0.3517 |
| 0.3659        | 29.41 | 3000 | 0.2809          | 0.3310 |
| 0.3065        | 34.31 | 3500 | 0.2882          | 0.3076 |
| 0.2739        | 39.22 | 4000 | 0.2632          | 0.2870 |
| 0.2516        | 44.12 | 4500 | 0.2872          | 0.2897 |
| 0.2316        | 49.02 | 5000 | 0.2875          | 0.2767 |
| 0.2159        | 53.92 | 5500 | 0.2953          | 0.2746 |
| 0.1957        | 58.82 | 6000 | 0.2955          | 0.2787 |
| 0.1997        | 63.73 | 6500 | 0.2963          | 0.2822 |
| 0.1852        | 68.63 | 7000 | 0.2910          | 0.2712 |


### Framework versions

- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1