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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
model-index:
- name: pic-20s_asr-scr_w2v2-base_001
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. -->
# pic-20s_asr-scr_w2v2-base_001
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: 1.4443
- Per: 0.1499
- Pcc: 0.6371
- Ctc Loss: 0.5406
- Mse Loss: 0.8841
## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 1
- seed: 2222
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2247
- training_steps: 22470
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Per | Pcc | Ctc Loss | Mse Loss |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
| 16.6841 | 3.0 | 2247 | 4.7118 | 0.9979 | 0.6160 | 3.7745 | 1.0013 |
| 4.2857 | 6.0 | 4494 | 4.2485 | 0.9979 | 0.6999 | 3.7428 | 0.6844 |
| 3.9118 | 9.0 | 6741 | 4.2032 | 0.9979 | 0.6863 | 3.7209 | 0.7501 |
| 3.5336 | 12.0 | 8988 | 3.8740 | 0.9976 | 0.6645 | 3.1591 | 0.9697 |
| 2.1131 | 15.0 | 11235 | 2.0043 | 0.2726 | 0.6564 | 1.1426 | 0.8936 |
| 0.9858 | 18.0 | 13482 | 1.6048 | 0.1817 | 0.6377 | 0.7083 | 0.8783 |
| 0.7106 | 21.0 | 15729 | 1.5797 | 0.1625 | 0.6447 | 0.6061 | 0.9394 |
| 0.5928 | 24.0 | 17976 | 1.4856 | 0.1552 | 0.6392 | 0.5624 | 0.8977 |
| 0.525 | 27.0 | 20223 | 1.4673 | 0.1515 | 0.6343 | 0.5471 | 0.8972 |
| 0.4862 | 30.0 | 22470 | 1.4443 | 0.1499 | 0.6371 | 0.5406 | 0.8841 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.2
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