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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: xlsr-wav2vec2-1
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. -->
# xlsr-wav2vec2-1
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5437
- Wer: 0.4412
## 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: 800
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.517 | 1.38 | 400 | 3.0431 | 1.0 |
| 1.8387 | 2.76 | 800 | 0.6552 | 0.7263 |
| 0.5971 | 4.14 | 1200 | 0.5308 | 0.5885 |
| 0.4153 | 5.52 | 1600 | 0.4667 | 0.5551 |
| 0.3388 | 6.9 | 2000 | 0.4428 | 0.5260 |
| 0.2803 | 8.28 | 2400 | 0.4915 | 0.5164 |
| 0.2613 | 9.65 | 2800 | 0.4904 | 0.4988 |
| 0.237 | 11.03 | 3200 | 0.4998 | 0.5075 |
| 0.2175 | 12.41 | 3600 | 0.4905 | 0.4983 |
| 0.1969 | 13.79 | 4000 | 0.4818 | 0.4877 |
| 0.1932 | 15.17 | 4400 | 0.5578 | 0.5006 |
| 0.1782 | 16.55 | 4800 | 0.4981 | 0.4949 |
| 0.1655 | 17.93 | 5200 | 0.4978 | 0.4940 |
| 0.1505 | 19.31 | 5600 | 0.5360 | 0.4896 |
| 0.1362 | 20.69 | 6000 | 0.5441 | 0.4709 |
| 0.1246 | 22.07 | 6400 | 0.5358 | 0.4650 |
| 0.1117 | 23.45 | 6800 | 0.5513 | 0.4716 |
| 0.107 | 24.83 | 7200 | 0.5344 | 0.4578 |
| 0.0963 | 26.21 | 7600 | 0.5073 | 0.4452 |
| 0.0846 | 27.59 | 8000 | 0.5335 | 0.4497 |
| 0.0799 | 28.96 | 8400 | 0.5437 | 0.4412 |
### Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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