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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_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. -->
# cmb-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: 0.1978
- Per: 0.1287
- Pcc: 0.6493
- Ctc Loss: 0.4014
- Mse Loss: 0.9499
## 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: 8928
- training_steps: 89280
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Per | Pcc | Ctc Loss | Mse Loss |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:|
| 11.3245 | 3.0 | 8928 | 4.4416 | 0.9956 | 0.6159 | 3.7640 | 0.8975 |
| 2.9636 | 6.0 | 17856 | 1.4930 | 0.1745 | 0.6638 | 0.6280 | 0.8352 |
| 1.0327 | 9.0 | 26784 | 1.3313 | 0.1461 | 0.6666 | 0.4797 | 0.8799 |
| 0.5448 | 12.0 | 35712 | 1.2880 | 0.1394 | 0.6530 | 0.4501 | 0.9425 |
| 0.1232 | 15.0 | 44640 | 1.0484 | 0.1354 | 0.6481 | 0.4289 | 0.8871 |
| -0.3248 | 18.0 | 53568 | 1.3777 | 0.1330 | 0.6373 | 0.4163 | 1.1622 |
| -0.7634 | 21.0 | 62496 | 1.0371 | 0.1312 | 0.6499 | 0.4094 | 1.0824 |
| -1.2089 | 24.0 | 71424 | 0.4166 | 0.1298 | 0.6454 | 0.4060 | 0.9053 |
| -1.613 | 27.0 | 80352 | 0.2751 | 0.1290 | 0.6473 | 0.4021 | 0.9426 |
| -1.8704 | 30.0 | 89280 | 0.1978 | 0.1287 | 0.6493 | 0.4014 | 0.9499 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.0.1
- Datasets 2.18.0
- Tokenizers 0.15.2
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