|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: wav2vec2-demo-F01-2 |
|
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-demo-F01-2 |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.6361 |
|
- Wer: 0.9025 |
|
|
|
## 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: 0.0001 |
|
- train_batch_size: 8 |
|
- 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: 1000 |
|
- num_epochs: 30 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:| |
|
| 23.7408 | 0.81 | 500 | 3.3782 | 1.0 | |
|
| 3.348 | 1.62 | 1000 | 2.9501 | 1.0 | |
|
| 2.8539 | 2.44 | 1500 | 2.6975 | 1.0 | |
|
| 2.311 | 3.25 | 2000 | 1.7770 | 1.3175 | |
|
| 1.5102 | 4.06 | 2500 | 1.3481 | 1.3515 | |
|
| 1.0616 | 4.87 | 3000 | 1.4306 | 1.2313 | |
|
| 0.8493 | 5.68 | 3500 | 1.2261 | 1.1701 | |
|
| 0.7058 | 6.49 | 4000 | 1.2132 | 1.1111 | |
|
| 0.6129 | 7.31 | 4500 | 1.4230 | 1.1429 | |
|
| 0.5513 | 8.12 | 5000 | 1.2003 | 1.0499 | |
|
| 0.4957 | 8.93 | 5500 | 1.5534 | 1.1043 | |
|
| 0.4456 | 9.74 | 6000 | 1.2315 | 1.0658 | |
|
| 0.4101 | 10.55 | 6500 | 1.1621 | 1.0680 | |
|
| 0.3776 | 11.36 | 7000 | 1.4302 | 1.0385 | |
|
| 0.3318 | 12.18 | 7500 | 1.3488 | 0.9977 | |
|
| 0.3189 | 12.99 | 8000 | 1.4050 | 1.0295 | |
|
| 0.3103 | 13.8 | 8500 | 1.4535 | 1.0385 | |
|
| 0.2791 | 14.61 | 9000 | 1.3318 | 1.0181 | |
|
| 0.2681 | 15.42 | 9500 | 1.5199 | 0.9909 | |
|
| 0.2352 | 16.23 | 10000 | 1.5019 | 1.0023 | |
|
| 0.235 | 17.05 | 10500 | 1.7984 | 0.9955 | |
|
| 0.2319 | 17.86 | 11000 | 1.3399 | 0.9705 | |
|
| 0.221 | 18.67 | 11500 | 1.8316 | 0.9342 | |
|
| 0.2154 | 19.48 | 12000 | 1.6837 | 0.9637 | |
|
| 0.1911 | 20.29 | 12500 | 1.6999 | 0.9388 | |
|
| 0.1754 | 21.1 | 13000 | 1.4801 | 0.9274 | |
|
| 0.1776 | 21.92 | 13500 | 1.7954 | 0.9206 | |
|
| 0.1616 | 22.73 | 14000 | 1.7891 | 0.9320 | |
|
| 0.1579 | 23.54 | 14500 | 1.5692 | 0.9116 | |
|
| 0.173 | 24.35 | 15000 | 1.4928 | 0.9048 | |
|
| 0.1561 | 25.16 | 15500 | 1.6492 | 0.9116 | |
|
| 0.1542 | 25.97 | 16000 | 1.7356 | 0.9048 | |
|
| 0.131 | 26.79 | 16500 | 1.7785 | 0.9048 | |
|
| 0.1295 | 27.6 | 17000 | 1.6532 | 0.9116 | |
|
| 0.1374 | 28.41 | 17500 | 1.6760 | 0.9093 | |
|
| 0.1186 | 29.22 | 18000 | 1.6361 | 0.9025 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.23.1 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 1.18.3 |
|
- Tokenizers 0.13.2 |
|
|
