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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
model-index:
- name: cmb-20s_asr-scr_w2v2-base_002
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. -->
# cmb-20s_asr-scr_w2v2-base_002
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: 0.2887
- Per: 0.1279
- Pcc: 0.6501
- Ctc Loss: 0.3968
- Mse Loss: 1.0164
## 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: 8928
- training_steps: 89280
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Per | Pcc | Ctc Loss | Mse Loss |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
| 11.516 | 3.0 | 8928 | 4.4204 | 0.9956 | 0.6302 | 3.7718 | 0.8695 |
| 2.6821 | 6.0 | 17856 | 1.4363 | 0.1800 | 0.6754 | 0.6151 | 0.8033 |
| 1.0205 | 9.0 | 26784 | 1.4608 | 0.1457 | 0.6734 | 0.4819 | 0.9911 |
| 0.5238 | 12.0 | 35712 | 1.1546 | 0.1375 | 0.6624 | 0.4382 | 0.8751 |
| 0.0849 | 15.0 | 44640 | 1.2248 | 0.1338 | 0.6576 | 0.4181 | 1.0163 |
| -0.3644 | 18.0 | 53568 | 1.4907 | 0.1314 | 0.6513 | 0.4077 | 1.2464 |
| -0.8166 | 21.0 | 62496 | 0.5897 | 0.1302 | 0.6518 | 0.4054 | 0.8912 |
| -1.2642 | 24.0 | 71424 | 0.5638 | 0.1286 | 0.6511 | 0.3985 | 0.9995 |
| -1.6765 | 27.0 | 80352 | 0.4494 | 0.1282 | 0.6490 | 0.3980 | 1.0442 |
| -1.9395 | 30.0 | 89280 | 0.2887 | 0.1279 | 0.6501 | 0.3968 | 1.0164 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.2
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