metadata
license: mit
base_model: intfloat/multilingual-e5-small
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: e5_finetuned
results: []
e5_finetuned
This model is a fine-tuned version of intfloat/multilingual-e5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0611
- Precision: 0.9494
- Recall: 0.8860
- F1: 0.9166
- Accuracy: 0.9799
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 0.0009 | 2 | 0.7141 | 0.125 | 1.0 | 0.2222 | 0.125 |
| 0.1046 | 0.9998 | 2334 | 0.0905 | 0.9564 | 0.8239 | 0.8852 | 0.9733 |
| 0.0786 | 2.0 | 4669 | 0.0734 | 0.9550 | 0.8540 | 0.9016 | 0.9767 |
| 0.0761 | 2.9998 | 7003 | 0.0690 | 0.9358 | 0.8834 | 0.9088 | 0.9778 |
| 0.0673 | 4.0 | 9338 | 0.0621 | 0.9594 | 0.8750 | 0.9152 | 0.9797 |
| 0.0709 | 4.9989 | 11670 | 0.0611 | 0.9494 | 0.8860 | 0.9166 | 0.9799 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1