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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_003
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_003
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: 1.4215
- Per: 0.1497
- Pcc: 0.6339
- Ctc Loss: 0.5259
- Mse Loss: 0.8821
## 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: 3333
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
| 17.0464 | 3.0 | 2247 | 5.0097 | 0.9979 | 0.6184 | 3.7876 | 1.2860 |
| 4.3019 | 6.0 | 4494 | 4.2229 | 0.9979 | 0.7055 | 3.7328 | 0.6675 |
| 3.9383 | 9.0 | 6741 | 4.1717 | 0.9979 | 0.7012 | 3.7059 | 0.7331 |
| 3.3316 | 12.0 | 8988 | 2.9515 | 0.6216 | 0.6761 | 2.3269 | 0.7956 |
| 1.5694 | 15.0 | 11235 | 1.8634 | 0.2235 | 0.6674 | 0.8822 | 0.9706 |
| 0.8929 | 18.0 | 13482 | 1.5733 | 0.1742 | 0.6392 | 0.6657 | 0.8867 |
| 0.6847 | 21.0 | 15729 | 1.6522 | 0.1613 | 0.6497 | 0.5817 | 1.0250 |
| 0.5739 | 24.0 | 17976 | 1.4394 | 0.1534 | 0.6165 | 0.5482 | 0.8750 |
| 0.5063 | 27.0 | 20223 | 1.4105 | 0.1510 | 0.6296 | 0.5322 | 0.8668 |
| 0.4701 | 30.0 | 22470 | 1.4215 | 0.1497 | 0.6339 | 0.5259 | 0.8821 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.0.1
- Datasets 2.18.0
- Tokenizers 0.15.2
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