File size: 2,350 Bytes
ee726bd |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 |
---
library_name: transformers
license: mit
base_model: intfloat/multilingual-e5-large-instruct
tags:
- generated_from_trainer
model-index:
- name: e5_EC_MultiLabel_08092025
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_EC_MultiLabel_08092025
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: 0.1035
- F1 Weighted: 0.9609
## 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_FUSED 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 |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|
| 0.822 | 1.0 | 359 | 0.4715 | 0.7472 |
| 0.4137 | 2.0 | 718 | 0.2841 | 0.8514 |
| 0.2836 | 3.0 | 1077 | 0.2275 | 0.8854 |
| 0.214 | 4.0 | 1436 | 0.1941 | 0.9035 |
| 0.1697 | 5.0 | 1795 | 0.1617 | 0.9244 |
| 0.1362 | 6.0 | 2154 | 0.1396 | 0.9361 |
| 0.1141 | 7.0 | 2513 | 0.1285 | 0.9408 |
| 0.0926 | 8.0 | 2872 | 0.1243 | 0.9476 |
| 0.0788 | 9.0 | 3231 | 0.1081 | 0.9542 |
| 0.0685 | 10.0 | 3590 | 0.1111 | 0.9574 |
| 0.0571 | 11.0 | 3949 | 0.1069 | 0.9613 |
| 0.0529 | 12.0 | 4308 | 0.1035 | 0.9609 |
### Framework versions
- Transformers 4.56.0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
|