| --- |
| library_name: transformers |
| license: mit |
| base_model: intfloat/multilingual-e5-large-instruct |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: e5_Eau_Multilabel_Topic_Sentiment |
| 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_Eau_Multilabel_Topic_Sentiment |
|
|
| 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: 0.1566 |
| - F1 Topic: 0.9104 |
| - F1 Sentiment: 0.8933 |
| - F1 Macro Avg: 0.9019 |
|
|
| ## 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: 1e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - 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 |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 20 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | F1 Topic | F1 Sentiment | F1 Macro Avg | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------------:|:------------:| |
| | 0.5731 | 1.0 | 148 | 0.4031 | 0.4584 | 0.6075 | 0.5330 | |
| | 0.2812 | 2.0 | 296 | 0.1726 | 0.7873 | 0.8019 | 0.7946 | |
| | 0.1396 | 3.0 | 444 | 0.1214 | 0.8694 | 0.8576 | 0.8635 | |
| | 0.0982 | 4.0 | 592 | 0.1244 | 0.8886 | 0.8643 | 0.8765 | |
| | 0.0732 | 5.0 | 740 | 0.1311 | 0.9118 | 0.8850 | 0.8984 | |
| | 0.0508 | 6.0 | 888 | 0.1566 | 0.9104 | 0.8933 | 0.9019 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.53.2 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 4.0.0 |
| - Tokenizers 0.21.2 |
|
|
