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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: 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. -->
# wav2vec2-1
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5980
- Wer: 0.4949
## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.2691 | 1.37 | 200 | 2.9045 | 1.0 |
| 1.6356 | 2.74 | 400 | 0.9277 | 0.8678 |
| 0.8062 | 4.11 | 600 | 0.8200 | 0.7776 |
| 0.5983 | 5.48 | 800 | 0.6829 | 0.7161 |
| 0.4863 | 6.85 | 1000 | 0.6205 | 0.6507 |
| 0.407 | 8.22 | 1200 | 0.6519 | 0.6763 |
| 0.3641 | 9.59 | 1400 | 0.5771 | 0.6088 |
| 0.3291 | 10.96 | 1600 | 0.6548 | 0.6202 |
| 0.2905 | 12.33 | 1800 | 0.6538 | 0.5828 |
| 0.2613 | 13.7 | 2000 | 0.6281 | 0.5864 |
| 0.2354 | 15.07 | 2200 | 0.5936 | 0.5630 |
| 0.2145 | 16.44 | 2400 | 0.5877 | 0.5699 |
| 0.2008 | 17.81 | 2600 | 0.5469 | 0.5488 |
| 0.1751 | 19.18 | 2800 | 0.6453 | 0.5584 |
| 0.169 | 20.55 | 3000 | 0.5871 | 0.5357 |
| 0.1521 | 21.92 | 3200 | 0.6063 | 0.5318 |
| 0.1426 | 23.29 | 3400 | 0.5609 | 0.5171 |
| 0.1287 | 24.66 | 3600 | 0.6056 | 0.5126 |
| 0.1236 | 26.03 | 3800 | 0.5994 | 0.5074 |
| 0.1138 | 27.4 | 4000 | 0.5980 | 0.4944 |
| 0.1083 | 28.77 | 4200 | 0.5980 | 0.4949 |
### Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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