humor_model_v4
This model is a fine-tuned version of facebook/hubert-large-ls960-ft on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6057
- Accuracy: 0.8675
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 | 0.6819 | 0.8735 |
0.6691 | 1.9048 | 10 | 0.6710 | 0.8735 |
0.6691 | 2.8571 | 15 | 0.6686 | 0.8735 |
0.6307 | 4.0 | 21 | 0.6559 | 0.8735 |
0.6307 | 4.9524 | 26 | 0.6401 | 0.8735 |
0.6172 | 5.9048 | 31 | 0.6264 | 0.8735 |
0.6172 | 6.8571 | 36 | 0.6148 | 0.8675 |
0.6053 | 8.0 | 42 | 0.6084 | 0.8675 |
0.6053 | 8.9524 | 47 | 0.6063 | 0.8614 |
0.5968 | 9.5238 | 50 | 0.6057 | 0.8675 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for rishiA/humor_model_v4
Base model
facebook/hubert-large-ls960-ft