Wav2Vec2ForSequenceClassification-finetuned-eos_poc5_ge-di-v7-meeting-v2
This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6822
- Accuracy: 0.6114
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 |
|---|---|---|---|---|
| 2.5858 | 0.9748 | 29 | 0.6455 | 0.6517 |
| 2.5709 | 1.9748 | 58 | 0.6422 | 0.6517 |
| 2.5285 | 2.9748 | 87 | 0.6421 | 0.6517 |
| 2.4906 | 3.9748 | 116 | 0.6335 | 0.6540 |
| 2.437 | 4.9748 | 145 | 0.6330 | 0.6517 |
| 2.3735 | 5.9748 | 174 | 0.6458 | 0.5972 |
| 2.1678 | 6.9748 | 203 | 0.6553 | 0.6114 |
| 2.1317 | 7.9748 | 232 | 0.6734 | 0.5900 |
| 2.0619 | 8.9748 | 261 | 0.6809 | 0.5806 |
| 1.9324 | 9.9748 | 290 | 0.6822 | 0.6114 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0