File size: 2,289 Bytes
c20b77b | 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 | ---
library_name: transformers
license: mit
base_model: intfloat/multilingual-e5-large-instruct
tags:
- generated_from_trainer
model-index:
- name: e5_Dechets_MultiLabel_11082025
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_Dechets_MultiLabel_11082025
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: 0.1865
- F1 Weighted: 0.9369
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|
| 0.9053 | 1.0 | 181 | 0.5982 | 0.7363 |
| 0.5249 | 2.0 | 362 | 0.3559 | 0.8555 |
| 0.3522 | 3.0 | 543 | 0.2938 | 0.8827 |
| 0.277 | 4.0 | 724 | 0.2611 | 0.9013 |
| 0.2244 | 5.0 | 905 | 0.2399 | 0.9118 |
| 0.1936 | 6.0 | 1086 | 0.2483 | 0.9133 |
| 0.165 | 7.0 | 1267 | 0.2163 | 0.9219 |
| 0.1422 | 8.0 | 1448 | 0.1924 | 0.9320 |
| 0.1232 | 9.0 | 1629 | 0.1878 | 0.9361 |
| 0.1096 | 10.0 | 1810 | 0.1913 | 0.9364 |
| 0.0975 | 11.0 | 1991 | 0.1865 | 0.9369 |
### Framework versions
- Transformers 4.55.0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.4
|