|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-large-xlsr-53 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Model_G_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. --> |
|
|
|
# Model_G_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: 0.7332 |
|
- Wer: 1.0098 |
|
- Cer: 0.7490 |
|
|
|
## 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: 0.0003 |
|
- 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: 500 |
|
- num_epochs: 30 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
|
| 3.5212 | 2.57 | 400 | 0.7741 | 1.0236 | 0.7838 | |
|
| 0.3158 | 5.14 | 800 | 0.6119 | 1.0085 | 0.7600 | |
|
| 0.1522 | 7.72 | 1200 | 0.6402 | 1.0215 | 0.7521 | |
|
| 0.102 | 10.29 | 1600 | 0.6226 | 1.0134 | 0.7540 | |
|
| 0.0752 | 12.86 | 2000 | 0.6474 | 1.0365 | 0.7501 | |
|
| 0.0627 | 15.43 | 2400 | 0.6617 | 1.0169 | 0.7503 | |
|
| 0.0535 | 18.01 | 2800 | 0.6818 | 1.0116 | 0.7495 | |
|
| 0.0432 | 20.58 | 3200 | 0.7056 | 1.0125 | 0.7536 | |
|
| 0.0383 | 23.15 | 3600 | 0.6953 | 1.0096 | 0.7448 | |
|
| 0.0347 | 25.72 | 4000 | 0.7217 | 1.0202 | 0.7457 | |
|
| 0.0301 | 28.3 | 4400 | 0.7332 | 1.0098 | 0.7490 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.31.0 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 1.18.3 |
|
- Tokenizers 0.13.3 |
|
|
