---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: apac_5sents_XLS-R_2
  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. -->

# apac_5sents_XLS-R_2

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: 274.3813
- Wer: 1.0

## 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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:---:|
| 281.5958      | 5.54   | 100  | 273.7941        | 1.0 |
| 281.366       | 11.11  | 200  | 269.9106        | 1.0 |
| 273.1232      | 16.65  | 300  | 263.4907        | 1.0 |
| 261.9693      | 22.22  | 400  | 249.4823        | 1.0 |
| 219.9941      | 27.76  | 500  | 176.5986        | 1.0 |
| 147.673       | 33.32  | 600  | 122.9458        | 1.0 |
| 114.1416      | 38.86  | 700  | 101.6788        | 1.0 |
| 99.6196       | 44.43  | 800  | 91.0054         | 1.0 |
| 90.5221       | 49.97  | 900  | 84.6282         | 1.0 |
| 85.6017       | 55.54  | 1000 | 80.2764         | 1.0 |
| 81.5146       | 61.11  | 1100 | 77.0657         | 1.0 |
| 77.7573       | 66.65  | 1200 | 74.5696         | 1.0 |
| 76.1933       | 72.22  | 1300 | 72.5473         | 1.0 |
| 73.6424       | 77.76  | 1400 | 70.8357         | 1.0 |
| 72.4248       | 83.32  | 1500 | 69.3329         | 1.0 |
| 70.3529       | 88.86  | 1600 | 67.9791         | 1.0 |
| 69.4685       | 94.43  | 1700 | 66.7548         | 1.0 |
| 68.0717       | 99.97  | 1800 | 65.6130         | 1.0 |
| 67.2376       | 105.54 | 1900 | 64.5488         | 1.0 |
| 66.0277       | 111.11 | 2000 | 63.5492         | 1.0 |
| 64.7994       | 116.65 | 2100 | 62.6000         | 1.0 |
| 64.0574       | 122.22 | 2200 | 61.7027         | 1.0 |
| 62.9425       | 127.76 | 2300 | 60.8545         | 1.0 |
| 62.254        | 133.32 | 2400 | 60.0502         | 1.0 |
| 61.3336       | 138.86 | 2500 | 59.2789         | 1.0 |
| 60.7559       | 144.43 | 2600 | 58.5486         | 1.0 |
| 59.7298       | 149.97 | 2700 | 57.8531         | 1.0 |
| 59.4008       | 155.54 | 2800 | 57.1906         | 1.0 |
| 58.6672       | 161.11 | 2900 | 56.5612         | 1.0 |
| 57.6835       | 166.65 | 3000 | 55.9709         | 1.0 |
| 57.4515       | 172.22 | 3100 | 55.4099         | 1.0 |
| 56.7266       | 177.76 | 3200 | 54.8743         | 1.0 |
| 56.3382       | 183.32 | 3300 | 54.3800         | 1.0 |
| 55.4538       | 188.86 | 3400 | 53.9105         | 1.0 |
| 55.4566       | 194.43 | 3500 | 53.4741         | 1.0 |
| 54.6733       | 199.97 | 3600 | 53.0646         | 1.0 |
| 54.5231       | 205.54 | 3700 | 52.6835         | 1.0 |
| 54.1944       | 211.11 | 3800 | 52.3376         | 1.0 |
| 53.5359       | 216.65 | 3900 | 52.0120         | 1.0 |
| 53.4527       | 222.22 | 4000 | 51.7225         | 1.0 |
| 53.0497       | 227.76 | 4100 | 51.4579         | 1.0 |
| 52.9911       | 233.32 | 4200 | 51.2190         | 1.0 |
| 52.3869       | 238.86 | 4300 | 51.0154         | 1.0 |
| 52.4158       | 244.43 | 4400 | 50.8332         | 1.0 |
| 52.1746       | 249.97 | 4500 | 50.6797         | 1.0 |
| 52.2056       | 255.54 | 4600 | 50.5553         | 1.0 |
| 52.1142       | 261.11 | 4700 | 50.4548         | 1.0 |
| 51.7802       | 266.65 | 4800 | 50.3846         | 1.0 |
| 51.9224       | 272.22 | 4900 | 50.3413         | 1.0 |
| 51.7253       | 277.76 | 5000 | 50.3258         | 1.0 |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.0.1+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3