---
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