---
library_name: transformers
base_model: MiMe-MeMo/MeMo-BERT-03
tags:
- generated_from_trainer
model-index:
- name: memobert3_ED
  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_ED

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: 0.7895
- F1-score: 0.9012

## 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   | 0.4129          | 0.8180   |
| No log        | 2.0   | 138  | 0.5440          | 0.8511   |
| No log        | 3.0   | 207  | 0.6458          | 0.8767   |
| No log        | 4.0   | 276  | 0.6689          | 0.8683   |
| No log        | 5.0   | 345  | 0.7171          | 0.8848   |
| No log        | 6.0   | 414  | 1.0837          | 0.8585   |
| No log        | 7.0   | 483  | 0.7652          | 0.8848   |
| 0.1451        | 8.0   | 552  | 0.7895          | 0.9012   |
| 0.1451        | 9.0   | 621  | 0.8248          | 0.8929   |
| 0.1451        | 10.0  | 690  | 0.8456          | 0.8929   |
| 0.1451        | 11.0  | 759  | 0.8626          | 0.8929   |
| 0.1451        | 12.0  | 828  | 0.8791          | 0.8929   |
| 0.1451        | 13.0  | 897  | 0.8929          | 0.8845   |
| 0.1451        | 14.0  | 966  | 0.9028          | 0.8845   |
| 0.0001        | 15.0  | 1035 | 0.9134          | 0.8845   |
| 0.0001        | 16.0  | 1104 | 0.9205          | 0.8845   |
| 0.0001        | 17.0  | 1173 | 0.9262          | 0.8845   |
| 0.0001        | 18.0  | 1242 | 0.9309          | 0.8845   |
| 0.0001        | 19.0  | 1311 | 0.9331          | 0.8845   |
| 0.0001        | 20.0  | 1380 | 0.9337          | 0.8845   |


### Framework versions

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