| --- |
| library_name: transformers |
| license: mit |
| base_model: intfloat/multilingual-e5-large-instruct |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: e5_Sentiment_EC_v2 |
| 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_Sentiment_EC_v2 |
| |
| 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: 0.7983 |
| - Accuracy: 0.9264 |
| - F1: 0.9272 |
| |
| ## 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: 2e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - 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 |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 20 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | 0.9261 | 1.0 | 60 | 0.4343 | 0.8738 | 0.8831 | |
| | 0.4464 | 2.0 | 120 | 0.5634 | 0.8780 | 0.8798 | |
| | 0.3124 | 3.0 | 180 | 0.4483 | 0.8833 | 0.8886 | |
| | 0.1974 | 4.0 | 240 | 0.6330 | 0.9169 | 0.9166 | |
| | 0.0894 | 5.0 | 300 | 0.5516 | 0.9317 | 0.9322 | |
| | 0.0702 | 6.0 | 360 | 0.5297 | 0.9338 | 0.9343 | |
| | 0.0359 | 7.0 | 420 | 0.7433 | 0.9338 | 0.9327 | |
| | 0.0269 | 8.0 | 480 | 0.7983 | 0.9264 | 0.9272 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.52.4 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.1 |
| |
