---
license: mit
base_model: intfloat/multilingual-e5-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: miner-24_e5
  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. -->

# miner-24_e5

This model is a fine-tuned version of [intfloat/multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8934
- Accuracy: 0.796
- Ball: 0.125
- Precision: 0.0995
- Recall: 0.125
- F1: 0.1108

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Ball  | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:---------:|:------:|:------:|
| 1.4223        | 1.0   | 624  | 0.8490          | 0.796    | 0.125 | 0.0995    | 0.125  | 0.1108 |
| 1.3854        | 2.0   | 1248 | 0.8556          | 0.796    | 0.125 | 0.0995    | 0.125  | 0.1108 |
| 1.3709        | 3.0   | 1872 | 0.8934          | 0.796    | 0.125 | 0.0995    | 0.125  | 0.1108 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1