e5_Eau_v2
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: 0.0466
- Accuracy: 0.9766
- F1: 0.9769
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 |
---|---|---|---|---|---|
0.5047 | 1.0 | 75 | 0.1616 | 0.9453 | 0.9454 |
0.1814 | 2.0 | 150 | 0.1131 | 0.9594 | 0.9599 |
0.1396 | 3.0 | 225 | 0.1037 | 0.9672 | 0.9672 |
0.1203 | 4.0 | 300 | 0.0632 | 0.9741 | 0.9741 |
0.1063 | 5.0 | 375 | 0.0584 | 0.9749 | 0.9752 |
0.0929 | 6.0 | 450 | 0.0486 | 0.9777 | 0.9776 |
0.0779 | 7.0 | 525 | 0.0466 | 0.9766 | 0.9769 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
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Base model
intfloat/multilingual-e5-large-instruct