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library_name: transformers
license: mit
base_model: intfloat/multilingual-e5-large-instruct
tags:
- generated_from_trainer
model-index:
- name: e5_RSE_MultiLabel_06082025
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# e5_RSE_MultiLabel_06082025
This model is a fine-tuned version of [intfloat/multilingual-e5-large-instruct](https://huggingface.co/intfloat/multilingual-e5-large-instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1417
- F1 Weighted: 0.9479
## 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-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|
| 0.9065 | 1.0 | 276 | 0.5238 | 0.7205 |
| 0.4792 | 2.0 | 552 | 0.3395 | 0.8138 |
| 0.3315 | 3.0 | 828 | 0.2634 | 0.8660 |
| 0.2536 | 4.0 | 1104 | 0.2347 | 0.8898 |
| 0.2039 | 5.0 | 1380 | 0.2079 | 0.9054 |
| 0.1671 | 6.0 | 1656 | 0.1819 | 0.9228 |
| 0.1403 | 7.0 | 1932 | 0.1779 | 0.9260 |
| 0.121 | 8.0 | 2208 | 0.1647 | 0.9340 |
| 0.1069 | 9.0 | 2484 | 0.1544 | 0.9404 |
| 0.0917 | 10.0 | 2760 | 0.1495 | 0.9456 |
| 0.0828 | 11.0 | 3036 | 0.1470 | 0.9461 |
| 0.0753 | 12.0 | 3312 | 0.1420 | 0.9481 |
| 0.0696 | 13.0 | 3588 | 0.1417 | 0.9479 |
### Framework versions
- Transformers 4.55.0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.4
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