|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: Wav2Vec2_Finetuned |
|
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_Finetuned |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9886 |
|
- Accuracy: 0.7247 |
|
|
|
## 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: 3e-05 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 128 |
|
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:| |
|
| 2.1066 | 0.9863 | 54 | 2.0550 | 0.3211 | |
|
| 1.7945 | 1.9817 | 108 | 1.8463 | 0.3858 | |
|
| 1.5042 | 2.9772 | 162 | 1.6106 | 0.4911 | |
|
| 1.3307 | 3.9909 | 217 | 1.3656 | 0.6199 | |
|
| 1.1295 | 4.9863 | 271 | 1.2506 | 0.6417 | |
|
| 1.0127 | 5.9817 | 325 | 1.2754 | 0.6211 | |
|
| 0.949 | 6.9772 | 379 | 1.0925 | 0.7041 | |
|
| 0.8618 | 7.9909 | 434 | 1.0693 | 0.7052 | |
|
| 0.7838 | 8.9863 | 488 | 1.0308 | 0.7138 | |
|
| 0.7813 | 9.9452 | 540 | 0.9886 | 0.7247 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.46.2 |
|
- Pytorch 2.5.1+cu121 |
|
- Datasets 3.1.0 |
|
- Tokenizers 0.20.3 |
|
|