|
|
--- |
|
|
license: apache-2.0 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: wav2vec2-base_toy_train_data_random_noise |
|
|
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_toy_train_data_random_noise |
|
|
|
|
|
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: 1.0909 |
|
|
- Wer: 0.7351 |
|
|
|
|
|
## 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: 16 |
|
|
- eval_batch_size: 8 |
|
|
- seed: 42 |
|
|
- gradient_accumulation_steps: 2 |
|
|
- total_train_batch_size: 32 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- lr_scheduler_warmup_steps: 1000 |
|
|
- num_epochs: 20 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
|
| 3.128 | 2.1 | 250 | 3.5052 | 1.0 | |
|
|
| 3.0423 | 4.2 | 500 | 2.9312 | 1.0 | |
|
|
| 1.4109 | 6.3 | 750 | 1.2618 | 0.8915 | |
|
|
| 0.9132 | 8.4 | 1000 | 1.1074 | 0.8436 | |
|
|
| 0.7146 | 10.5 | 1250 | 1.0397 | 0.7876 | |
|
|
| 0.5418 | 12.6 | 1500 | 1.0359 | 0.7662 | |
|
|
| 0.4649 | 14.7 | 1750 | 1.0469 | 0.7467 | |
|
|
| 0.4127 | 16.8 | 2000 | 1.0655 | 0.7404 | |
|
|
| 0.3881 | 18.9 | 2250 | 1.0909 | 0.7351 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.17.0 |
|
|
- Pytorch 1.11.0+cu102 |
|
|
- Datasets 2.0.0 |
|
|
- Tokenizers 0.11.6 |
|
|
|
