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---
license: apache-2.0
base_model: facebook/wav2vec2-large
tags:
- generated_from_trainer
model-index:
- name: k2e-20s_asr-scr_w2v2-large_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. -->
# k2e-20s_asr-scr_w2v2-large_001
This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7509
- Per: 0.1453
- Pcc: 0.6324
- Ctc Loss: 0.5111
- Mse Loss: 1.2263
## 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: 1111
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2235
- training_steps: 22350
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Per | Pcc | Ctc Loss | Mse Loss |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
| 14.3265 | 3.0 | 2235 | 4.6461 | 0.9890 | 0.6160 | 3.6176 | 1.0856 |
| 3.4446 | 6.01 | 4470 | 2.8757 | 0.3498 | 0.6516 | 1.0729 | 1.7895 |
| 1.5549 | 9.01 | 6705 | 2.0517 | 0.1846 | 0.6507 | 0.6672 | 1.3503 |
| 1.1194 | 12.02 | 8940 | 1.8625 | 0.1650 | 0.6443 | 0.5914 | 1.2388 |
| 0.9031 | 15.02 | 11175 | 1.8899 | 0.1554 | 0.6312 | 0.5473 | 1.3054 |
| 0.7614 | 18.02 | 13410 | 1.5491 | 0.1522 | 0.6307 | 0.5349 | 1.0200 |
| 0.6483 | 21.03 | 15645 | 1.8357 | 0.1481 | 0.6304 | 0.5215 | 1.2852 |
| 0.5561 | 24.03 | 17880 | 2.0576 | 0.1468 | 0.6263 | 0.5191 | 1.4774 |
| 0.5108 | 27.04 | 20115 | 1.8949 | 0.1452 | 0.6351 | 0.5090 | 1.3489 |
| 0.4778 | 30.04 | 22350 | 1.7509 | 0.1453 | 0.6324 | 0.5111 | 1.2263 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.2
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