|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-base |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: pic-20s_asr-scr_w2v2-base_004 |
|
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_004 |
|
|
|
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: 1.4351 |
|
- Per: 0.1529 |
|
- Pcc: 0.6741 |
|
- Ctc Loss: 0.5362 |
|
- Mse Loss: 0.8881 |
|
|
|
## 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: 1234 |
|
- 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 | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:| |
|
| 17.1513 | 3.0 | 2247 | 4.7158 | 0.9979 | 0.6302 | 3.7674 | 1.0133 | |
|
| 4.2201 | 6.0 | 4494 | 4.2724 | 0.9979 | 0.7096 | 3.7172 | 0.7331 | |
|
| 3.7967 | 9.0 | 6741 | 4.3058 | 0.9975 | 0.6875 | 3.6713 | 0.8900 | |
|
| 3.0022 | 12.0 | 8988 | 2.4439 | 0.5310 | 0.6794 | 1.8297 | 0.7356 | |
|
| 1.3508 | 15.0 | 11235 | 1.8496 | 0.2221 | 0.6786 | 0.8430 | 0.9894 | |
|
| 0.825 | 18.0 | 13482 | 1.5793 | 0.1815 | 0.6751 | 0.6577 | 0.8999 | |
|
| 0.6436 | 21.0 | 15729 | 1.7474 | 0.1690 | 0.6748 | 0.5867 | 1.1030 | |
|
| 0.5476 | 24.0 | 17976 | 1.4824 | 0.1589 | 0.6730 | 0.5570 | 0.9069 | |
|
| 0.4889 | 27.0 | 20223 | 1.3293 | 0.1544 | 0.6701 | 0.5413 | 0.7952 | |
|
| 0.4593 | 30.0 | 22470 | 1.4351 | 0.1529 | 0.6741 | 0.5362 | 0.8881 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.1 |
|
- Pytorch 2.0.1 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
