---
base_model: MiMe-MeMo/MeMo-BERT-03
tags:
- generated_from_trainer
model-index:
- name: memo3_FGN
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# memo3_FGN

This model is a fine-tuned version of [MiMe-MeMo/MeMo-BERT-03](https://huggingface.co/MiMe-MeMo/MeMo-BERT-03) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3348
- F1-score: 0.8316

## 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   | 120  | 0.4934          | 0.8027   |
| No log        | 2.0   | 240  | 0.5542          | 0.8121   |
| No log        | 3.0   | 360  | 0.8229          | 0.8168   |
| No log        | 4.0   | 480  | 0.9300          | 0.8123   |
| 0.4028        | 5.0   | 600  | 1.1413          | 0.8057   |
| 0.4028        | 6.0   | 720  | 1.3327          | 0.7989   |
| 0.4028        | 7.0   | 840  | 1.5178          | 0.7851   |
| 0.4028        | 8.0   | 960  | 1.1979          | 0.8299   |
| 0.0435        | 9.0   | 1080 | 1.2149          | 0.8307   |
| 0.0435        | 10.0  | 1200 | 1.2327          | 0.8302   |
| 0.0435        | 11.0  | 1320 | 1.2521          | 0.8312   |
| 0.0435        | 12.0  | 1440 | 1.2734          | 0.8304   |
| 0.0238        | 13.0  | 1560 | 1.3348          | 0.8316   |
| 0.0238        | 14.0  | 1680 | 1.3715          | 0.8181   |
| 0.0238        | 15.0  | 1800 | 1.4095          | 0.8064   |
| 0.0238        | 16.0  | 1920 | 1.4157          | 0.8179   |
| 0.0099        | 17.0  | 2040 | 1.4234          | 0.8179   |
| 0.0099        | 18.0  | 2160 | 1.4038          | 0.8127   |
| 0.0099        | 19.0  | 2280 | 1.4404          | 0.8117   |
| 0.0099        | 20.0  | 2400 | 1.4436          | 0.8117   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1