|
--- |
|
base_model: MiMe-MeMo/MeMo-BERT-02 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: MeMo_BERT-WSD-02 |
|
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-WSD-02 |
|
|
|
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: 3.4274 |
|
- F1-score: 0.3523 |
|
|
|
## 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 | 61 | 1.6387 | 0.1229 | |
|
| No log | 2.0 | 122 | 1.4760 | 0.2016 | |
|
| No log | 3.0 | 183 | 1.4995 | 0.2754 | |
|
| No log | 4.0 | 244 | 1.9750 | 0.2519 | |
|
| No log | 5.0 | 305 | 2.3945 | 0.3115 | |
|
| No log | 6.0 | 366 | 2.9512 | 0.2336 | |
|
| No log | 7.0 | 427 | 3.3875 | 0.2933 | |
|
| No log | 8.0 | 488 | 3.4274 | 0.3523 | |
|
| 0.6662 | 9.0 | 549 | 3.8142 | 0.3244 | |
|
| 0.6662 | 10.0 | 610 | 4.3089 | 0.3271 | |
|
| 0.6662 | 11.0 | 671 | 4.4936 | 0.2806 | |
|
| 0.6662 | 12.0 | 732 | 4.4328 | 0.2893 | |
|
| 0.6662 | 13.0 | 793 | 4.8685 | 0.2353 | |
|
| 0.6662 | 14.0 | 854 | 4.4432 | 0.3018 | |
|
| 0.6662 | 15.0 | 915 | 4.6090 | 0.2820 | |
|
| 0.6662 | 16.0 | 976 | 4.5783 | 0.2871 | |
|
| 0.0033 | 17.0 | 1037 | 4.6179 | 0.2871 | |
|
| 0.0033 | 18.0 | 1098 | 4.7173 | 0.2847 | |
|
| 0.0033 | 19.0 | 1159 | 4.7240 | 0.3029 | |
|
| 0.0033 | 20.0 | 1220 | 4.7167 | 0.3029 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|