masa-preskripsi-multiclass1
This model is a fine-tuned version of intfloat/multilingual-e5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8187
- Accuracy: 0.6241
- F1: 0.6048
- Precision: 0.6138
- Recall: 0.6028
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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.8656 | 1.0 | 7397 | 0.8187 | 0.6241 | 0.6048 | 0.6138 | 0.6028 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for senmasa/masa-preskripsi-multiclass1
Base model
intfloat/multilingual-e5-small