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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: apac_5sents_XLS-R_5e-5
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_5e-5
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: 1.6693
- Wer: 0.6607
## 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: 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: 20000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 98.1859 | 11.11 | 200 | 75.6610 | 1.0 |
| 66.0186 | 22.22 | 400 | 52.7194 | 1.0 |
| 40.6772 | 33.32 | 600 | 26.2206 | 1.0 |
| 16.4279 | 44.43 | 800 | 8.3596 | 1.0 |
| 6.1402 | 55.54 | 1000 | 5.3091 | 1.0 |
| 4.733 | 66.65 | 1200 | 4.5618 | 1.0 |
| 3.4737 | 77.76 | 1400 | 3.4971 | 1.0 |
| 1.6412 | 88.86 | 1600 | 2.7199 | 0.9219 |
| 0.8524 | 99.97 | 1800 | 2.0043 | 0.9241 |
| 0.6227 | 111.11 | 2000 | 2.1371 | 0.9330 |
| 0.4834 | 122.22 | 2200 | 1.6094 | 0.9196 |
| 0.3944 | 133.32 | 2400 | 2.2378 | 0.9531 |
| 0.2975 | 144.43 | 2600 | 1.7241 | 0.8862 |
| 0.194 | 155.54 | 2800 | 1.8496 | 0.7679 |
| 0.1211 | 166.65 | 3000 | 1.4915 | 0.6808 |
| 0.0866 | 177.76 | 3200 | 1.9463 | 0.6429 |
| 0.0696 | 188.86 | 3400 | 2.0191 | 0.5737 |
| 0.0563 | 199.97 | 3600 | 2.4305 | 0.6562 |
| 0.0461 | 211.11 | 3800 | 1.6485 | 0.6138 |
| 0.0413 | 222.22 | 4000 | 2.2569 | 0.6272 |
### Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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