metadata
library_name: transformers
license: mit
base_model: intfloat/multilingual-e5-large-instruct
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: e5_EC_v2
results: []
e5_EC_v2
This model is a fine-tuned version of intfloat/multilingual-e5-large-instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3848
- Accuracy: 0.9181
- F1: 0.9183
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 |
|---|---|---|---|---|---|
| 2.0685 | 1.0 | 81 | 1.1118 | 0.7713 | 0.7709 |
| 0.5172 | 2.0 | 162 | 0.3434 | 0.8910 | 0.8922 |
| 0.2829 | 3.0 | 243 | 0.2663 | 0.9189 | 0.9192 |
| 0.1237 | 4.0 | 324 | 0.2979 | 0.9158 | 0.9157 |
| 0.065 | 5.0 | 405 | 0.3067 | 0.9274 | 0.9275 |
| 0.0452 | 6.0 | 486 | 0.3848 | 0.9181 | 0.9183 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1