---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-azeri-colab
  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-xls-r-300m-azeri-colab

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: 0.7742
- Wer: 0.2862

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 9.778         | 1.48  | 100  | 4.5181          | 1.0    |
| 3.5462        | 2.96  | 200  | 3.2628          | 1.0    |
| 3.1799        | 4.44  | 300  | 3.1485          | 1.0    |
| 2.1997        | 5.93  | 400  | 1.0459          | 0.7941 |
| 0.6827        | 7.41  | 500  | 0.5548          | 0.5073 |
| 0.4084        | 8.89  | 600  | 0.7589          | 0.4241 |
| 0.2698        | 10.37 | 700  | 0.4763          | 0.4137 |
| 0.1896        | 11.85 | 800  | 0.4656          | 0.3703 |
| 0.1518        | 13.33 | 900  | 0.5659          | 0.3457 |
| 0.1268        | 14.81 | 1000 | 0.5960          | 0.3488 |
| 0.1067        | 16.3  | 1100 | 0.6429          | 0.3279 |
| 0.0866        | 17.78 | 1200 | 0.5888          | 0.3310 |
| 0.0761        | 19.26 | 1300 | 0.8183          | 0.3208 |
| 0.0659        | 20.74 | 1400 | 0.7465          | 0.3079 |
| 0.0581        | 22.22 | 1500 | 0.7774          | 0.3109 |
| 0.0496        | 23.7  | 1600 | 0.8111          | 0.3006 |
| 0.0448        | 25.19 | 1700 | 0.7206          | 0.2952 |
| 0.0398        | 26.67 | 1800 | 0.7885          | 0.2926 |
| 0.0374        | 28.15 | 1900 | 0.7724          | 0.2862 |
| 0.0345        | 29.63 | 2000 | 0.7742          | 0.2862 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3