---
library_name: transformers
base_model: MiMe-MeMo/MeMo-BERT-03
tags:
- generated_from_trainer
model-index:
- name: memobert3_ED1
  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. -->

# memobert3_ED1

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: 0.6065
- F1-score: 0.9098

## 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   | 69   | 0.3808          | 0.8439   |
| No log        | 2.0   | 138  | 0.4234          | 0.8432   |
| No log        | 3.0   | 207  | 0.4577          | 0.9013   |
| No log        | 4.0   | 276  | 0.6278          | 0.8851   |
| No log        | 5.0   | 345  | 0.6449          | 0.8517   |
| No log        | 6.0   | 414  | 0.7495          | 0.8678   |
| No log        | 7.0   | 483  | 0.6065          | 0.9098   |
| 0.1663        | 8.0   | 552  | 0.6217          | 0.9098   |
| 0.1663        | 9.0   | 621  | 0.6420          | 0.9098   |
| 0.1663        | 10.0  | 690  | 0.6514          | 0.9098   |
| 0.1663        | 11.0  | 759  | 0.6627          | 0.9098   |
| 0.1663        | 12.0  | 828  | 0.6726          | 0.9098   |
| 0.1663        | 13.0  | 897  | 0.6828          | 0.9016   |
| 0.1663        | 14.0  | 966  | 0.6904          | 0.9016   |
| 0.0001        | 15.0  | 1035 | 0.6942          | 0.9016   |
| 0.0001        | 16.0  | 1104 | 0.6976          | 0.9016   |
| 0.0001        | 17.0  | 1173 | 0.7007          | 0.9016   |
| 0.0001        | 18.0  | 1242 | 0.7027          | 0.9016   |
| 0.0001        | 19.0  | 1311 | 0.7038          | 0.9016   |
| 0.0001        | 20.0  | 1380 | 0.7037          | 0.9016   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1