|
|
--- |
|
|
license: apache-2.0 |
|
|
base_model: facebook/wav2vec2-base-960h |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- wer |
|
|
model-index: |
|
|
- name: wav2vec2-base-nsc-demo-4 |
|
|
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. --> |
|
|
|
|
|
# wav2vec2-base-nsc-demo-4 |
|
|
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.3016 |
|
|
- Wer: 0.1720 |
|
|
|
|
|
## 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: 5.9591386586384804e-05 |
|
|
- train_batch_size: 32 |
|
|
- eval_batch_size: 8 |
|
|
- seed: 42 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- lr_scheduler_warmup_steps: 100 |
|
|
- num_epochs: 51 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
|
| 0.7542 | 2.27 | 50 | 0.3351 | 0.1948 | |
|
|
| 0.3912 | 4.55 | 100 | 0.3016 | 0.1720 | |
|
|
| 0.2497 | 6.82 | 150 | 0.3247 | 0.1757 | |
|
|
| 0.201 | 9.09 | 200 | 0.3111 | 0.1728 | |
|
|
| 0.1602 | 11.36 | 250 | 0.3259 | 0.1723 | |
|
|
| 0.1334 | 13.64 | 300 | 0.3431 | 0.1765 | |
|
|
| 0.1083 | 15.91 | 350 | 0.3413 | 0.1726 | |
|
|
| 0.1114 | 18.18 | 400 | 0.4089 | 0.1768 | |
|
|
| 0.0828 | 20.45 | 450 | 0.3531 | 0.1765 | |
|
|
| 0.0926 | 22.73 | 500 | 0.3481 | 0.1755 | |
|
|
| 0.093 | 25.0 | 550 | 0.3379 | 0.1742 | |
|
|
| 0.0772 | 27.27 | 600 | 0.3628 | 0.1779 | |
|
|
| 0.0701 | 29.55 | 650 | 0.3747 | 0.1773 | |
|
|
| 0.0736 | 31.82 | 700 | 0.3834 | 0.1808 | |
|
|
| 0.0607 | 34.09 | 750 | 0.3747 | 0.1742 | |
|
|
| 0.0629 | 36.36 | 800 | 0.3683 | 0.1734 | |
|
|
| 0.0713 | 38.64 | 850 | 0.3671 | 0.1744 | |
|
|
| 0.0728 | 40.91 | 900 | 0.3632 | 0.1749 | |
|
|
| 0.0696 | 43.18 | 950 | 0.3615 | 0.1731 | |
|
|
| 0.0638 | 45.45 | 1000 | 0.3591 | 0.1755 | |
|
|
| 0.0552 | 47.73 | 1050 | 0.3608 | 0.1779 | |
|
|
| 0.0578 | 50.0 | 1100 | 0.3630 | 0.1752 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.33.0 |
|
|
- Pytorch 2.0.0 |
|
|
- Datasets 2.1.0 |
|
|
- Tokenizers 0.13.3 |
|
|
|
