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---
license: mit
base_model: intfloat/multilingual-e5-small
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: e5_finetuned
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_finetuned
This model is a fine-tuned version of [intfloat/multilingual-e5-small](https://huggingface.co/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
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