|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- precision |
|
- recall |
|
- f1 |
|
base_model: distilbert-base-multilingual-cased |
|
model-index: |
|
- name: distilbertmultilang |
|
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. --> |
|
|
|
# distilbertmultilang |
|
|
|
This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.5628 |
|
- Accuracy: 0.7527 |
|
- Precision: 0.7353 |
|
- Recall: 0.6867 |
|
- F1: 0.6967 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 999 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
|
| 0.4753 | 1.0 | 761 | 0.5657 | 0.7471 | 0.7146 | 0.6782 | 0.6831 | |
|
| 0.0881 | 2.0 | 1522 | 0.6042 | 0.7728 | 0.7387 | 0.7289 | 0.7329 | |
|
| 0.2734 | 3.0 | 2283 | 0.6275 | 0.7757 | 0.7431 | 0.7504 | 0.7459 | |
|
| 0.0468 | 4.0 | 3044 | 0.9842 | 0.7599 | 0.7362 | 0.7048 | 0.7140 | |
|
| 0.0037 | 5.0 | 3805 | 1.0992 | 0.7715 | 0.7402 | 0.7364 | 0.7374 | |
|
| 0.3644 | 6.0 | 4566 | 1.2696 | 0.7521 | 0.7460 | 0.6853 | 0.6928 | |
|
| 0.0078 | 7.0 | 5327 | 1.3667 | 0.7646 | 0.7329 | 0.7273 | 0.7293 | |
|
| 0.0021 | 8.0 | 6088 | 1.5628 | 0.7527 | 0.7353 | 0.6867 | 0.6967 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.2 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.17.1 |
|
- Tokenizers 0.15.2 |
|
|
