---
license: apache-2.0
tags:
- automatic-speech-recognition
- /workspace/data/uk/noizy_student_1/
- generated_from_trainer
model-index:
- name: ''
  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. -->

# 

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the /WORKSPACE/DATA/UK/NOIZY_STUDENT_1/ - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1285
- Wer: 0.1821
- Cer: 0.0342

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Cer    | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:------:|:---------------:|:------:|
| 1.2323        | 3.22  | 500   | 0.0797 | 0.2816          | 0.4133 |
| 0.9826        | 6.45  | 1000  | 0.0514 | 0.1970          | 0.2688 |
| 0.8628        | 9.67  | 1500  | 0.0474 | 0.1649          | 0.2485 |
| 0.8348        | 12.9  | 2000  | 0.0467 | 0.1605          | 0.2460 |
| 0.8186        | 16.13 | 2500  | 0.0469 | 0.1608          | 0.2469 |
| 0.8011        | 19.35 | 3000  | 0.1620 | 0.2412          | 0.0468 |
| 0.807         | 22.58 | 3500  | 0.1737 | 0.2524          | 0.0498 |
| 0.7758        | 25.8  | 4000  | 0.1709 | 0.2536          | 0.0498 |
| 0.7923        | 29.03 | 4500  | 0.1645 | 0.2436          | 0.0474 |
| 0.7717        | 32.26 | 5000  | 0.1811 | 0.2636          | 0.0524 |
| 0.7447        | 35.48 | 5500  | 0.1635 | 0.2405          | 0.0468 |
| 0.7267        | 38.71 | 6000  | 0.1578 | 0.2354          | 0.0462 |
| 0.7046        | 41.93 | 6500  | 0.1555 | 0.2296          | 0.0444 |
| 0.6896        | 45.16 | 7000  | 0.1548 | 0.2272          | 0.0439 |
| 0.6575        | 48.38 | 7500  | 0.1432 | 0.2096          | 0.0399 |
| 0.6264        | 51.61 | 8000  | 0.1466 | 0.2056          | 0.0398 |
| 0.589         | 54.83 | 8500  | 0.1351 | 0.1943          | 0.0371 |
| 0.573         | 58.06 | 9000  | 0.1387 | 0.1934          | 0.0365 |
| 0.5537        | 61.29 | 9500  | 0.1328 | 0.1883          | 0.0353 |
| 0.544         | 64.51 | 10000 | 0.1285 | 0.1821          | 0.0342 |


### Framework versions

- Transformers 4.17.0.dev0
- Pytorch 1.10.2
- Datasets 1.18.4.dev0
- Tokenizers 0.11.0