|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: w2v2-base-pretrained_lr1e-4_at0.7_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_lr1e-4_at0.7_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: 6.2022 |
|
- Wer: 1.0580 |
|
|
|
## 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: 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 |
|
- num_epochs: 60 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 18.007 | 4.46 | 250 | 4.3814 | 1.0 | |
|
| 3.2628 | 8.93 | 500 | 3.8568 | 1.0 | |
|
| 3.1079 | 13.39 | 750 | 3.9328 | 1.0 | |
|
| 1.4764 | 17.86 | 1000 | 2.7696 | 1.0384 | |
|
| 0.2321 | 22.32 | 1250 | 4.2808 | 1.0507 | |
|
| 0.1312 | 26.79 | 1500 | 4.8707 | 1.0529 | |
|
| 0.0793 | 31.25 | 1750 | 5.2587 | 1.0558 | |
|
| 0.0546 | 35.71 | 2000 | 5.6739 | 1.0541 | |
|
| 0.0401 | 40.18 | 2250 | 5.7379 | 1.0494 | |
|
| 0.0303 | 44.64 | 2500 | 5.8382 | 1.0558 | |
|
| 0.0255 | 49.11 | 2750 | 6.0859 | 1.0567 | |
|
| 0.0223 | 53.57 | 3000 | 6.0789 | 1.0558 | |
|
| 0.019 | 58.04 | 3250 | 6.2022 | 1.0580 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.0 |
|
- Pytorch 2.0.0 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|