---
license: mit
tags:
- generated_from_trainer
base_model: BAAI/bge-m3-retromae
metrics:
- accuracy
model-index:
- name: bge-m3-retromae-zeroshot-v2.0-2024-04-02-09-26
  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. -->

# bge-m3-retromae-zeroshot-v2.0-2024-04-02-09-26

This model is a fine-tuned version of [BAAI/bge-m3-retromae](https://huggingface.co/BAAI/bge-m3-retromae) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1873
- F1 Macro: 0.6439
- F1 Micro: 0.7032
- Accuracy Balanced: 0.6808
- Accuracy: 0.7032
- Precision Macro: 0.6635
- Recall Macro: 0.6808
- Precision Micro: 0.7032
- Recall Micro: 0.7032

## 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: 9e-06
- train_batch_size: 4
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- 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: 0.06
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
| 0.2461        | 1.0   | 33914 | 0.3735          | 0.8313   | 0.8456   | 0.8329            | 0.8456   | 0.8298          | 0.8329       | 0.8456          | 0.8456       |
| 0.1947        | 2.0   | 67828 | 0.3949          | 0.8370   | 0.8515   | 0.8371            | 0.8515   | 0.8370          | 0.8371       | 0.8515          | 0.8515       |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2