transformers pytorch tensorboard wav2vec2 automatic-speech-recognition generated_from_trainer dataset:lucas-meyer/asr_xh endpoints_compatible region:us
---
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: seq-xls-r-fleurs_zu-run3-asr_xh-run6
  results: []
datasets:
- lucas-meyer/asr_xh
---

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# seq-xls-r-fleurs_zu-run3-asr_xh-run6

This model is a fine-tuned version of [lucas-meyer/xls-r-fleurs_zu-run3](https://huggingface.co/lucas-meyer/xls-r-fleurs_zu-run3) on the asr_xh dataset.
It achieves the following results:
- Wer (Validation): 52.22%
- Wer (Test): 55.30%

### 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer (Train)   |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 9.168         | 0.64  | 100  | 3.3818          | 1.0    |
| 3.1636        | 1.27  | 200  | 2.9143          | 1.0    |
| 1.4923        | 1.91  | 300  | 0.5876          | 0.6829 |
| 0.6236        | 2.55  | 400  | 0.4900          | 0.6200 |
| 0.4883        | 3.18  | 500  | 0.4963          | 0.6210 |
| 0.4404        | 3.82  | 600  | 0.4000          | 0.5517 |
| 0.3469        | 4.46  | 700  | 0.4189          | 0.5543 |
| 0.319         | 5.1   | 800  | 0.3833          | 0.5212 |
| 0.254         | 5.73  | 900  | 0.4483          | 0.5471 |
| 0.2501        | 6.37  | 1000 | 0.4029          | 0.5115 |
| 0.2121        | 7.01  | 1100 | 0.4397          | 0.5105 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3