---
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-sinhala-aug-data-with-original-split-part3
  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-sinhala-aug-data-with-original-split-part3

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0246
- Wer: 0.0367

## 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: 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
- num_epochs: 21

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 5.8396        | 0.27  | 400   | 0.9752          | 0.8374 |
| 0.6967        | 0.54  | 800   | 0.3812          | 0.5935 |
| 0.4806        | 0.81  | 1200  | 0.3368          | 0.4757 |
| 0.3996        | 1.09  | 1600  | 0.1994          | 0.3143 |
| 0.3497        | 1.36  | 2000  | 0.1684          | 0.2564 |
| 0.3372        | 1.63  | 2400  | 0.1586          | 0.2419 |
| 0.312         | 1.9   | 2800  | 0.1413          | 0.2227 |
| 0.2797        | 2.17  | 3200  | 0.1466          | 0.2273 |
| 0.2554        | 2.44  | 3600  | 0.1543          | 0.2366 |
| 0.2613        | 2.71  | 4000  | 0.1450          | 0.2326 |
| 0.2399        | 2.99  | 4400  | 0.1238          | 0.2030 |
| 0.2125        | 3.26  | 4800  | 0.0989          | 0.1610 |
| 0.2144        | 3.53  | 5200  | 0.0984          | 0.1612 |
| 0.212         | 3.8   | 5600  | 0.0876          | 0.1507 |
| 0.1964        | 4.07  | 6000  | 0.1017          | 0.1753 |
| 0.1814        | 4.34  | 6400  | 0.0967          | 0.1654 |
| 0.1772        | 4.61  | 6800  | 0.0956          | 0.1631 |
| 0.1748        | 4.88  | 7200  | 0.0870          | 0.1483 |
| 0.1706        | 5.16  | 7600  | 0.0771          | 0.1306 |
| 0.1545        | 5.43  | 8000  | 0.0653          | 0.1199 |
| 0.1627        | 5.7   | 8400  | 0.0600          | 0.1103 |
| 0.1541        | 5.97  | 8800  | 0.0589          | 0.1068 |
| 0.1382        | 6.24  | 9200  | 0.0710          | 0.1231 |
| 0.1397        | 6.51  | 9600  | 0.0651          | 0.1248 |
| 0.1345        | 6.78  | 10000 | 0.0670          | 0.1194 |
| 0.1281        | 7.06  | 10400 | 0.0541          | 0.1006 |
| 0.1315        | 7.33  | 10800 | 0.0559          | 0.1062 |
| 0.1234        | 7.6   | 11200 | 0.0528          | 0.0970 |
| 0.1248        | 7.87  | 11600 | 0.0448          | 0.0865 |
| 0.115         | 8.14  | 12000 | 0.0546          | 0.0994 |
| 0.1143        | 8.41  | 12400 | 0.0595          | 0.1086 |
| 0.1169        | 8.68  | 12800 | 0.0485          | 0.0874 |
| 0.1165        | 8.96  | 13200 | 0.0524          | 0.0977 |
| 0.1035        | 9.23  | 13600 | 0.0445          | 0.0837 |
| 0.1017        | 9.5   | 14000 | 0.0413          | 0.0792 |
| 0.109         | 9.77  | 14400 | 0.0420          | 0.0833 |
| 0.1018        | 10.04 | 14800 | 0.0454          | 0.0823 |
| 0.0929        | 10.31 | 15200 | 0.0429          | 0.0786 |
| 0.0956        | 10.58 | 15600 | 0.0403          | 0.0772 |
| 0.0986        | 10.85 | 16000 | 0.0468          | 0.0906 |
| 0.0941        | 11.13 | 16400 | 0.0362          | 0.0694 |
| 0.0845        | 11.4  | 16800 | 0.0387          | 0.0702 |
| 0.0955        | 11.67 | 17200 | 0.0351          | 0.0627 |
| 0.089         | 11.94 | 17600 | 0.0361          | 0.0675 |
| 0.0806        | 12.21 | 18000 | 0.0381          | 0.0685 |
| 0.0803        | 12.48 | 18400 | 0.0370          | 0.0675 |
| 0.0839        | 12.75 | 18800 | 0.0333          | 0.0619 |
| 0.0834        | 13.03 | 19200 | 0.0334          | 0.0577 |
| 0.0779        | 13.3  | 19600 | 0.0358          | 0.0621 |
| 0.0773        | 13.57 | 20000 | 0.0330          | 0.0565 |
| 0.0717        | 13.84 | 20400 | 0.0350          | 0.0625 |
| 0.0737        | 14.11 | 20800 | 0.0355          | 0.0603 |
| 0.075         | 14.38 | 21200 | 0.0361          | 0.0626 |
| 0.0715        | 14.65 | 21600 | 0.0314          | 0.0575 |
| 0.0722        | 14.93 | 22000 | 0.0310          | 0.0575 |
| 0.0666        | 15.2  | 22400 | 0.0314          | 0.0559 |
| 0.0672        | 15.47 | 22800 | 0.0307          | 0.0535 |
| 0.0664        | 15.74 | 23200 | 0.0315          | 0.0552 |
| 0.0678        | 16.01 | 23600 | 0.0312          | 0.0548 |
| 0.0616        | 16.28 | 24000 | 0.0315          | 0.0527 |
| 0.0644        | 16.55 | 24400 | 0.0269          | 0.0481 |
| 0.062         | 16.82 | 24800 | 0.0308          | 0.0513 |
| 0.0584        | 17.1  | 25200 | 0.0294          | 0.0502 |
| 0.0563        | 17.37 | 25600 | 0.0294          | 0.0492 |
| 0.0547        | 17.64 | 26000 | 0.0281          | 0.0452 |
| 0.056         | 17.91 | 26400 | 0.0279          | 0.0451 |
| 0.0572        | 18.18 | 26800 | 0.0293          | 0.0460 |
| 0.0544        | 18.45 | 27200 | 0.0283          | 0.0464 |
| 0.052         | 18.72 | 27600 | 0.0274          | 0.0438 |
| 0.0533        | 19.0  | 28000 | 0.0264          | 0.0413 |
| 0.046         | 19.27 | 28400 | 0.0276          | 0.0412 |
| 0.0498        | 19.54 | 28800 | 0.0282          | 0.0419 |
| 0.0454        | 19.81 | 29200 | 0.0279          | 0.0417 |
| 0.0483        | 20.08 | 29600 | 0.0260          | 0.0396 |
| 0.0447        | 20.35 | 30000 | 0.0267          | 0.0418 |
| 0.0424        | 20.62 | 30400 | 0.0249          | 0.0373 |
| 0.0409        | 20.9  | 30800 | 0.0246          | 0.0367 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2