wav2vec2-base-finetuned-sentiment-mesd-v2
This model is a fine-tuned version of 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