|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: w2v2-base-pretrained_lr5e-5_at0.8_da0.025 |
|
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_at0.8_da0.025 |
|
|
|
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: 3.9947 |
|
- Wer: 1.0205 |
|
|
|
## 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 | |
|
|:-------------:|:------:|:----:|:---------------:|:------:| |
|
| 36.9594 | 125.0 | 250 | 12.4193 | 1.0 | |
|
| 5.8739 | 250.0 | 500 | 3.2963 | 1.0 | |
|
| 3.1532 | 375.0 | 750 | 3.1231 | 1.0 | |
|
| 3.0639 | 500.0 | 1000 | 3.1060 | 1.0 | |
|
| 3.013 | 625.0 | 1250 | 3.1074 | 1.0 | |
|
| 2.9755 | 750.0 | 1500 | 3.1334 | 1.0 | |
|
| 2.94 | 875.0 | 1750 | 3.1535 | 1.0 | |
|
| 2.8802 | 1000.0 | 2000 | 3.0883 | 1.0 | |
|
| 2.474 | 1125.0 | 2250 | 2.8111 | 1.0009 | |
|
| 1.3378 | 1250.0 | 2500 | 3.0612 | 1.0038 | |
|
| 0.7759 | 1375.0 | 2750 | 3.4681 | 1.0068 | |
|
| 0.594 | 1500.0 | 3000 | 3.6791 | 1.0337 | |
|
| 0.5034 | 1625.0 | 3250 | 3.8161 | 1.0226 | |
|
| 0.4518 | 1750.0 | 3500 | 3.8285 | 1.0081 | |
|
| 0.4139 | 1875.0 | 3750 | 3.9486 | 1.0201 | |
|
| 0.3953 | 2000.0 | 4000 | 3.9947 | 1.0205 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.0 |
|
- Pytorch 2.0.0 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|
