---
base_model: MiMe-MeMo/MeMo-BERT-02
tags:
- generated_from_trainer
model-index:
- name: MeMo_BERT-SA_2
  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. -->

# MeMo_BERT-SA_2

This model is a fine-tuned version of [MiMe-MeMo/MeMo-BERT-02](https://huggingface.co/MiMe-MeMo/MeMo-BERT-02) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4358
- F1-score: 0.5924

## 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: 5e-05
- 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1-score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 265  | 1.0171          | 0.5029   |
| 0.9806        | 2.0   | 530  | 0.9884          | 0.5416   |
| 0.9806        | 3.0   | 795  | 1.1255          | 0.5477   |
| 0.6405        | 4.0   | 1060 | 1.0771          | 0.5716   |
| 0.6405        | 5.0   | 1325 | 1.4358          | 0.5924   |
| 0.3872        | 6.0   | 1590 | 2.0203          | 0.5780   |
| 0.3872        | 7.0   | 1855 | 2.4784          | 0.5730   |
| 0.2014        | 8.0   | 2120 | 2.7627          | 0.5735   |
| 0.2014        | 9.0   | 2385 | 3.1488          | 0.5733   |
| 0.0888        | 10.0  | 2650 | 3.2253          | 0.5636   |
| 0.0888        | 11.0  | 2915 | 3.4722          | 0.5488   |
| 0.0563        | 12.0  | 3180 | 3.6568          | 0.5718   |
| 0.0563        | 13.0  | 3445 | 3.8553          | 0.5676   |
| 0.0188        | 14.0  | 3710 | 3.8721          | 0.5572   |
| 0.0188        | 15.0  | 3975 | 3.9256          | 0.5782   |
| 0.0021        | 16.0  | 4240 | 3.9991          | 0.5802   |
| 0.0032        | 17.0  | 4505 | 4.0370          | 0.5798   |
| 0.0032        | 18.0  | 4770 | 4.1400          | 0.5746   |
| 0.0012        | 19.0  | 5035 | 4.1422          | 0.5740   |
| 0.0012        | 20.0  | 5300 | 4.1453          | 0.5742   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2