---
license: mit
base_model: MoritzLaurer/bge-m3-zeroshot-v2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: nli-finetuning-laurer-immigration-classification
  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. -->

# nli-finetuning-laurer-immigration-classification

This model is a fine-tuned version of [MoritzLaurer/bge-m3-zeroshot-v2.0](https://huggingface.co/MoritzLaurer/bge-m3-zeroshot-v2.0) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5578
- Accuracy: 0.9032
- F1 Macro: 0.8969
- Accuracy Balanced: 0.8913
- F1 Micro: 0.9032
- Precision Macro: 0.9048
- Recall Macro: 0.8913
- Precision Micro: 0.9032
- Recall Micro: 0.9032

## 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: 80
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.25
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Accuracy Balanced | F1 Micro | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
| No log        | 1.0   | 151  | 0.3342          | 0.8763   | 0.8679   | 0.8619            | 0.8763   | 0.8769          | 0.8619       | 0.8763          | 0.8763       |
| No log        | 2.0   | 302  | 0.4733          | 0.8710   | 0.8680   | 0.8793            | 0.8710   | 0.8644          | 0.8793       | 0.8710          | 0.8710       |
| No log        | 3.0   | 453  | 0.5168          | 0.8978   | 0.8895   | 0.8796            | 0.8978   | 0.9073          | 0.8796       | 0.8978          | 0.8978       |
| 0.4084        | 4.0   | 604  | 0.5300          | 0.8871   | 0.8813   | 0.8804            | 0.8871   | 0.8823          | 0.8804       | 0.8871          | 0.8871       |
| 0.4084        | 5.0   | 755  | 0.5578          | 0.9032   | 0.8969   | 0.8913            | 0.9032   | 0.9048          | 0.8913       | 0.9032          | 0.9032       |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.5.0+cu121
- Datasets 2.14.7
- Tokenizers 0.13.3