| --- |
| library_name: transformers |
| license: mit |
| base_model: intfloat/multilingual-e5-large-instruct |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: e5_Main_topic_v1 |
| 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_Main_topic_v1 |
| |
| 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: 0.0357 |
| - Accuracy: 0.9871 |
| - F1: 0.9872 |
| |
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | 0.3915 | 1.0 | 335 | 0.2420 | 0.9269 | 0.9269 | |
| | 0.1777 | 2.0 | 670 | 0.0943 | 0.9682 | 0.9683 | |
| | 0.1244 | 3.0 | 1005 | 0.0757 | 0.9745 | 0.9745 | |
| | 0.103 | 4.0 | 1340 | 0.0751 | 0.9762 | 0.9763 | |
| | 0.0881 | 5.0 | 1675 | 0.0860 | 0.9717 | 0.9717 | |
| | 0.0771 | 6.0 | 2010 | 0.0454 | 0.9852 | 0.9852 | |
| | 0.0663 | 7.0 | 2345 | 0.0450 | 0.9851 | 0.9852 | |
| | 0.0634 | 8.0 | 2680 | 0.0454 | 0.9839 | 0.9839 | |
| | 0.0614 | 9.0 | 3015 | 0.0357 | 0.9871 | 0.9872 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.50.3 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.5.0 |
| - Tokenizers 0.21.1 |
|
|
