|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-large |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-large-sw-cv-100hr-v3 |
|
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-large-sw-cv-100hr-v3 |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.8721 |
|
- Model Preparation Time: 0.0042 |
|
- Wer: 0.9997 |
|
- Cer: 0.9176 |
|
|
|
## 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_ratio: 0.1 |
|
- num_epochs: 120 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer | Cer | |
|
|:-------------:|:-------:|:-----:|:---------------:|:----------------------:|:------:|:------:| |
|
| 4.0159 | 0.9998 | 2079 | 2.7894 | 0.0042 | 0.9999 | 0.9048 | |
|
| 2.8122 | 2.0 | 4159 | 2.8360 | 0.0042 | 1.0 | 1.0 | |
|
| 2.8312 | 2.9998 | 6238 | 2.8331 | 0.0042 | 1.0 | 1.0 | |
|
| 2.8295 | 4.0 | 8318 | 2.8340 | 0.0042 | 1.0 | 1.0 | |
|
| 2.8306 | 4.9998 | 10397 | 2.8309 | 0.0042 | 1.0 | 1.0 | |
|
| 2.8301 | 6.0 | 12477 | 2.8451 | 0.0042 | 1.0 | 1.0 | |
|
| 2.8305 | 6.9998 | 14556 | 2.8320 | 0.0042 | 1.0 | 1.0 | |
|
| 2.8547 | 8.0 | 16636 | 2.8626 | 0.0042 | 1.0 | 1.0 | |
|
| 2.8611 | 8.9998 | 18715 | 2.8569 | 0.0042 | 1.0 | 1.0 | |
|
| 2.8596 | 10.0 | 20795 | 2.8573 | 0.0042 | 1.0 | 1.0 | |
|
| 2.861 | 10.9998 | 22874 | 2.8570 | 0.0042 | 1.0 | 1.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.0 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
