|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-large-robust-ft-libri-960h |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: wav2vec2-large-robust-ft-libri-960h-finetuned-ravdess-v2 |
|
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-robust-ft-libri-960h-finetuned-ravdess-v2 |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-large-robust-ft-libri-960h](https://huggingface.co/facebook/wav2vec2-large-robust-ft-libri-960h) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.0280 |
|
- Accuracy: 0.6146 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- 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: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 2.0786 | 1.0 | 36 | 2.0692 | 0.1597 | |
|
| 2.0578 | 2.0 | 72 | 2.0555 | 0.1979 | |
|
| 1.9903 | 3.0 | 108 | 1.9172 | 0.2882 | |
|
| 1.8052 | 4.0 | 144 | 1.7975 | 0.2951 | |
|
| 1.7221 | 5.0 | 180 | 1.6602 | 0.4028 | |
|
| 1.5773 | 6.0 | 216 | 1.6362 | 0.4479 | |
|
| 1.4785 | 7.0 | 252 | 1.4675 | 0.4965 | |
|
| 1.3828 | 8.0 | 288 | 1.3735 | 0.5 | |
|
| 1.2352 | 9.0 | 324 | 1.2886 | 0.5278 | |
|
| 1.159 | 10.0 | 360 | 1.2184 | 0.5521 | |
|
| 1.073 | 11.0 | 396 | 1.1456 | 0.5556 | |
|
| 1.0127 | 12.0 | 432 | 1.1864 | 0.5694 | |
|
| 0.9374 | 13.0 | 468 | 1.1865 | 0.5625 | |
|
| 0.8622 | 14.0 | 504 | 1.1745 | 0.5660 | |
|
| 0.8704 | 15.0 | 540 | 1.1563 | 0.5694 | |
|
| 0.8607 | 16.0 | 576 | 1.0466 | 0.5938 | |
|
| 0.8228 | 17.0 | 612 | 1.0457 | 0.6007 | |
|
| 0.8521 | 18.0 | 648 | 1.0280 | 0.6146 | |
|
| 0.8248 | 19.0 | 684 | 1.0399 | 0.6146 | |
|
| 0.7901 | 20.0 | 720 | 1.0402 | 0.6111 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.31.0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.14.4 |
|
- Tokenizers 0.13.3 |
|
|
