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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: xlsr-wav2vec2-3
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-wav2vec2-3
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: 0.4201
- Wer: 0.3998
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 5.0117 | 0.68 | 400 | 3.0284 | 0.9999 |
| 2.6502 | 1.35 | 800 | 1.0868 | 0.9374 |
| 0.9362 | 2.03 | 1200 | 0.5216 | 0.6491 |
| 0.6675 | 2.7 | 1600 | 0.4744 | 0.5837 |
| 0.5799 | 3.38 | 2000 | 0.4400 | 0.5802 |
| 0.5196 | 4.05 | 2400 | 0.4266 | 0.5314 |
| 0.4591 | 4.73 | 2800 | 0.3808 | 0.5190 |
| 0.4277 | 5.41 | 3200 | 0.3987 | 0.5036 |
| 0.4125 | 6.08 | 3600 | 0.3902 | 0.5040 |
| 0.3797 | 6.76 | 4000 | 0.4105 | 0.5025 |
| 0.3606 | 7.43 | 4400 | 0.3975 | 0.4823 |
| 0.3554 | 8.11 | 4800 | 0.3733 | 0.4747 |
| 0.3373 | 8.78 | 5200 | 0.3737 | 0.4726 |
| 0.3252 | 9.46 | 5600 | 0.3795 | 0.4736 |
| 0.3192 | 10.14 | 6000 | 0.3935 | 0.4736 |
| 0.3012 | 10.81 | 6400 | 0.3974 | 0.4648 |
| 0.2972 | 11.49 | 6800 | 0.4497 | 0.4724 |
| 0.2873 | 12.16 | 7200 | 0.4645 | 0.4843 |
| 0.2849 | 12.84 | 7600 | 0.4461 | 0.4709 |
| 0.274 | 13.51 | 8000 | 0.4002 | 0.4695 |
| 0.2709 | 14.19 | 8400 | 0.4188 | 0.4627 |
| 0.2619 | 14.86 | 8800 | 0.3987 | 0.4646 |
| 0.2545 | 15.54 | 9200 | 0.4083 | 0.4668 |
| 0.2477 | 16.22 | 9600 | 0.4525 | 0.4728 |
| 0.2455 | 16.89 | 10000 | 0.4148 | 0.4515 |
| 0.2281 | 17.57 | 10400 | 0.4304 | 0.4514 |
| 0.2267 | 18.24 | 10800 | 0.4077 | 0.4446 |
| 0.2136 | 18.92 | 11200 | 0.4209 | 0.4445 |
| 0.2032 | 19.59 | 11600 | 0.4543 | 0.4534 |
| 0.1999 | 20.27 | 12000 | 0.4184 | 0.4373 |
| 0.1898 | 20.95 | 12400 | 0.4044 | 0.4424 |
| 0.1846 | 21.62 | 12800 | 0.4098 | 0.4288 |
| 0.1796 | 22.3 | 13200 | 0.4047 | 0.4262 |
| 0.1715 | 22.97 | 13600 | 0.4077 | 0.4189 |
| 0.1641 | 23.65 | 14000 | 0.4162 | 0.4248 |
| 0.1615 | 24.32 | 14400 | 0.4392 | 0.4222 |
| 0.1575 | 25.0 | 14800 | 0.4296 | 0.4185 |
| 0.1456 | 25.68 | 15200 | 0.4363 | 0.4129 |
| 0.1461 | 26.35 | 15600 | 0.4305 | 0.4124 |
| 0.1422 | 27.03 | 16000 | 0.4237 | 0.4086 |
| 0.1378 | 27.7 | 16400 | 0.4294 | 0.4051 |
| 0.1326 | 28.38 | 16800 | 0.4311 | 0.4051 |
| 0.1286 | 29.05 | 17200 | 0.4153 | 0.3992 |
| 0.1283 | 29.73 | 17600 | 0.4201 | 0.3998 |
### Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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