humor_model_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: 0.2683
- Accuracy: 0.9639
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.9524 | 5 | 0.6652 | 0.9157 |
| 0.6722 | 1.9048 | 10 | 0.5931 | 0.9217 |
| 0.6722 | 2.8571 | 15 | 0.5272 | 0.9337 |
| 0.5461 | 4.0 | 21 | 0.4712 | 0.8554 |
| 0.5461 | 4.9524 | 26 | 0.3943 | 0.8916 |
| 0.3891 | 5.9048 | 31 | 0.3369 | 0.9337 |
| 0.3891 | 6.8571 | 36 | 0.3099 | 0.9398 |
| 0.2976 | 8.0 | 42 | 0.2811 | 0.9578 |
| 0.2976 | 8.9524 | 47 | 0.2713 | 0.9578 |
| 0.2393 | 9.5238 | 50 | 0.2683 | 0.9639 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for rishiA/humor_model_v2
Base model
facebook/wav2vec2-base