|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: wav2vec2-base-finetuned-sentiment-mesd-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-base-finetuned-sentiment-mesd-v2 |
|
|
|
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: 1.7213 |
|
- Accuracy: 0.3923 |
|
|
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 1.25e-05 |
|
- train_batch_size: 64 |
|
- eval_batch_size: 40 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 256 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| No log | 0.86 | 3 | 1.7961 | 0.1462 | |
|
| 1.9685 | 1.86 | 6 | 1.7932 | 0.1692 | |
|
| 1.9685 | 2.86 | 9 | 1.7891 | 0.2 | |
|
| 2.1386 | 3.86 | 12 | 1.7820 | 0.2923 | |
|
| 1.9492 | 4.86 | 15 | 1.7750 | 0.2923 | |
|
| 1.9492 | 5.86 | 18 | 1.7684 | 0.2846 | |
|
| 2.1143 | 6.86 | 21 | 1.7624 | 0.3231 | |
|
| 2.1143 | 7.86 | 24 | 1.7561 | 0.3308 | |
|
| 2.0945 | 8.86 | 27 | 1.7500 | 0.3462 | |
|
| 1.9121 | 9.86 | 30 | 1.7443 | 0.3385 | |
|
| 1.9121 | 10.86 | 33 | 1.7386 | 0.3231 | |
|
| 2.0682 | 11.86 | 36 | 1.7328 | 0.3231 | |
|
| 2.0682 | 12.86 | 39 | 1.7272 | 0.3769 | |
|
| 2.0527 | 13.86 | 42 | 1.7213 | 0.3923 | |
|
| 1.8705 | 14.86 | 45 | 1.7154 | 0.3846 | |
|
| 1.8705 | 15.86 | 48 | 1.7112 | 0.3846 | |
|
| 2.0263 | 16.86 | 51 | 1.7082 | 0.3769 | |
|
| 2.0263 | 17.86 | 54 | 1.7044 | 0.3846 | |
|
| 2.0136 | 18.86 | 57 | 1.7021 | 0.3846 | |
|
| 1.8429 | 19.86 | 60 | 1.7013 | 0.3846 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.17.0 |
|
- Pytorch 1.10.0+cu111 |
|
- Datasets 2.0.0 |
|
- Tokenizers 0.11.6 |
|
|
