e5_Main_topic_v1
This model is a fine-tuned version of intfloat/multilingual-e5-large-instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0357
- Accuracy: 0.9871
- F1: 0.9872
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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: 100
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.3915 | 1.0 | 335 | 0.2420 | 0.9269 | 0.9269 |
0.1777 | 2.0 | 670 | 0.0943 | 0.9682 | 0.9683 |
0.1244 | 3.0 | 1005 | 0.0757 | 0.9745 | 0.9745 |
0.103 | 4.0 | 1340 | 0.0751 | 0.9762 | 0.9763 |
0.0881 | 5.0 | 1675 | 0.0860 | 0.9717 | 0.9717 |
0.0771 | 6.0 | 2010 | 0.0454 | 0.9852 | 0.9852 |
0.0663 | 7.0 | 2345 | 0.0450 | 0.9851 | 0.9852 |
0.0634 | 8.0 | 2680 | 0.0454 | 0.9839 | 0.9839 |
0.0614 | 9.0 | 3015 | 0.0357 | 0.9871 | 0.9872 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
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Model tree for Ludo33/e5_Main_topic_v1
Base model
intfloat/multilingual-e5-large-instruct