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---
license: apache-2.0
base_model: facebook/wav2vec2-large-lv60
tags:
- generated_from_trainer
model-index:
- name: k2e-20s_asr-scr_w2v2-large-lv60_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-lv60_001
This model is a fine-tuned version of [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.9960
- Per: 0.9491
- Pcc: 0.4581
- Ctc Loss: 2.9538
- Mse Loss: 1.3478
## 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: 2235
- training_steps: 22350
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Per | Pcc | Ctc Loss | Mse Loss |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
| 30.007 | 3.0 | 2235 | 4.9713 | 0.9890 | 0.4691 | 3.8731 | 1.1616 |
| 4.5436 | 6.01 | 4470 | 4.8907 | 0.9890 | 0.4458 | 3.7192 | 1.3424 |
| 4.1973 | 9.01 | 6705 | 4.7504 | 0.9890 | 0.4791 | 3.6454 | 1.3436 |
| 3.9659 | 12.02 | 8940 | 4.9631 | 0.9627 | 0.3953 | 3.5684 | 1.6631 |
| 3.7945 | 15.02 | 11175 | 4.6238 | 0.9627 | 0.3228 | 3.5522 | 1.3937 |
| 3.657 | 18.02 | 13410 | 4.8315 | 0.9627 | 0.3795 | 3.4947 | 1.6564 |
| 3.4943 | 21.03 | 15645 | 4.5083 | 0.9626 | 0.4295 | 3.3623 | 1.4824 |
| 3.3082 | 24.03 | 17880 | 4.1212 | 0.9625 | 0.4469 | 3.1651 | 1.2958 |
| 3.1432 | 27.04 | 20115 | 4.1271 | 0.9586 | 0.4566 | 3.0120 | 1.4192 |
| 3.0438 | 30.04 | 22350 | 3.9960 | 0.9491 | 0.4581 | 2.9538 | 1.3478 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.2
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