|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: w2v2-base-pretrained_lr5e-5_at0.6_da1 |
|
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. --> |
|
|
|
# w2v2-base-pretrained_lr5e-5_at0.6_da1 |
|
|
|
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: 1.4078 |
|
- Wer: 0.1662 |
|
|
|
## 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: 5e-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: 1000 |
|
- training_steps: 4000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 25.5608 | 4.24 | 250 | 20.1943 | 1.0 | |
|
| 5.6218 | 8.47 | 500 | 3.4933 | 1.0 | |
|
| 3.134 | 12.71 | 750 | 3.1332 | 1.0 | |
|
| 3.0842 | 16.95 | 1000 | 3.1196 | 1.0 | |
|
| 2.6714 | 21.19 | 1250 | 1.4095 | 0.9932 | |
|
| 0.5642 | 25.42 | 1500 | 0.6028 | 0.4327 | |
|
| 0.2724 | 29.66 | 1750 | 0.7355 | 0.2396 | |
|
| 0.1676 | 33.9 | 2000 | 0.9693 | 0.2264 | |
|
| 0.1247 | 38.14 | 2250 | 1.0615 | 0.2008 | |
|
| 0.0945 | 42.37 | 2500 | 1.2612 | 0.1841 | |
|
| 0.0784 | 46.61 | 2750 | 1.1492 | 0.1850 | |
|
| 0.0672 | 50.85 | 3000 | 1.3113 | 0.1751 | |
|
| 0.0567 | 55.08 | 3250 | 1.3594 | 0.1721 | |
|
| 0.0507 | 59.32 | 3500 | 1.4195 | 0.1721 | |
|
| 0.0478 | 63.56 | 3750 | 1.3916 | 0.1670 | |
|
| 0.0445 | 67.8 | 4000 | 1.4078 | 0.1662 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.0 |
|
- Pytorch 2.0.0 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|
