|
--- |
|
base_model: aubmindlab/bert-base-arabertv02 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: arabert_cross_vocabulary_task5_fold4 |
|
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. --> |
|
|
|
# arabert_cross_vocabulary_task5_fold4 |
|
|
|
This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5724 |
|
- Qwk: 0.8274 |
|
- Mse: 0.5724 |
|
|
|
## 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: 2e-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: 1 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | |
|
|:-------------:|:------:|:----:|:---------------:|:-------:|:------:| |
|
| No log | 0.0323 | 2 | 4.0786 | -0.0202 | 4.0786 | |
|
| No log | 0.0645 | 4 | 2.3283 | 0.0109 | 2.3283 | |
|
| No log | 0.0968 | 6 | 1.2785 | 0.2841 | 1.2785 | |
|
| No log | 0.1290 | 8 | 0.8433 | 0.4083 | 0.8433 | |
|
| No log | 0.1613 | 10 | 1.0059 | 0.5899 | 1.0059 | |
|
| No log | 0.1935 | 12 | 1.1298 | 0.6125 | 1.1298 | |
|
| No log | 0.2258 | 14 | 0.8824 | 0.7014 | 0.8824 | |
|
| No log | 0.2581 | 16 | 0.9194 | 0.7028 | 0.9194 | |
|
| No log | 0.2903 | 18 | 0.9116 | 0.7100 | 0.9116 | |
|
| No log | 0.3226 | 20 | 0.6668 | 0.7739 | 0.6668 | |
|
| No log | 0.3548 | 22 | 0.4256 | 0.7812 | 0.4256 | |
|
| No log | 0.3871 | 24 | 0.4050 | 0.7574 | 0.4050 | |
|
| No log | 0.4194 | 26 | 0.5814 | 0.7955 | 0.5814 | |
|
| No log | 0.4516 | 28 | 1.0279 | 0.7514 | 1.0279 | |
|
| No log | 0.4839 | 30 | 1.0452 | 0.7607 | 1.0452 | |
|
| No log | 0.5161 | 32 | 0.7165 | 0.8089 | 0.7165 | |
|
| No log | 0.5484 | 34 | 0.4458 | 0.7951 | 0.4458 | |
|
| No log | 0.5806 | 36 | 0.3735 | 0.7660 | 0.3735 | |
|
| No log | 0.6129 | 38 | 0.3982 | 0.7985 | 0.3982 | |
|
| No log | 0.6452 | 40 | 0.5173 | 0.8081 | 0.5173 | |
|
| No log | 0.6774 | 42 | 0.7723 | 0.7985 | 0.7723 | |
|
| No log | 0.7097 | 44 | 0.9254 | 0.7695 | 0.9254 | |
|
| No log | 0.7419 | 46 | 1.0677 | 0.7448 | 1.0677 | |
|
| No log | 0.7742 | 48 | 1.0524 | 0.7448 | 1.0524 | |
|
| No log | 0.8065 | 50 | 0.9408 | 0.7762 | 0.9408 | |
|
| No log | 0.8387 | 52 | 0.8100 | 0.7901 | 0.8100 | |
|
| No log | 0.8710 | 54 | 0.7061 | 0.8033 | 0.7061 | |
|
| No log | 0.9032 | 56 | 0.6220 | 0.8252 | 0.6220 | |
|
| No log | 0.9355 | 58 | 0.5830 | 0.8299 | 0.5830 | |
|
| No log | 0.9677 | 60 | 0.5721 | 0.8239 | 0.5721 | |
|
| No log | 1.0 | 62 | 0.5724 | 0.8274 | 0.5724 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.0 |
|
- Pytorch 2.4.0 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
