---
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: 1.6537
- F1-score: 0.5806

## 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   | 297  | 0.9994          | 0.4947   |
| 0.9854        | 2.0   | 594  | 1.0281          | 0.5454   |
| 0.9854        | 3.0   | 891  | 1.1639          | 0.5563   |
| 0.6507        | 4.0   | 1188 | 1.6537          | 0.5806   |
| 0.6507        | 5.0   | 1485 | 1.7769          | 0.5688   |
| 0.404         | 6.0   | 1782 | 2.2283          | 0.5678   |
| 0.1759        | 7.0   | 2079 | 2.7271          | 0.5659   |
| 0.1759        | 8.0   | 2376 | 3.2521          | 0.5701   |
| 0.0906        | 9.0   | 2673 | 3.2777          | 0.5655   |
| 0.0906        | 10.0  | 2970 | 3.3451          | 0.5696   |
| 0.0717        | 11.0  | 3267 | 3.7121          | 0.5610   |
| 0.0299        | 12.0  | 3564 | 3.8619          | 0.5420   |
| 0.0299        | 13.0  | 3861 | 3.9670          | 0.5654   |
| 0.02          | 14.0  | 4158 | 4.2349          | 0.5409   |
| 0.02          | 15.0  | 4455 | 4.2491          | 0.5549   |
| 0.0074        | 16.0  | 4752 | 4.4144          | 0.5467   |
| 0.006         | 17.0  | 5049 | 4.3564          | 0.5663   |
| 0.006         | 18.0  | 5346 | 4.5443          | 0.5616   |
| 0.004         | 19.0  | 5643 | 4.5436          | 0.5424   |
| 0.004         | 20.0  | 5940 | 4.5248          | 0.5582   |


### Framework versions

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