|
--- |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
base_model: xlm-roberta-base |
|
model-index: |
|
- name: mbti-career |
|
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. --> |
|
|
|
# mbti-career |
|
|
|
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3516 |
|
|
|
## 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 |
|
- lr_scheduler_warmup_steps: 300 |
|
- num_epochs: 15 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 0.6547 | 0.59 | 100 | 0.6169 | |
|
| 0.5967 | 1.18 | 200 | 0.5943 | |
|
| 0.5872 | 1.76 | 300 | 0.5696 | |
|
| 0.554 | 2.35 | 400 | 0.5287 | |
|
| 0.5041 | 2.94 | 500 | 0.4890 | |
|
| 0.4773 | 3.53 | 600 | 0.4895 | |
|
| 0.4691 | 4.12 | 700 | 0.4840 | |
|
| 0.4253 | 4.71 | 800 | 0.4573 | |
|
| 0.4002 | 5.29 | 900 | 0.4240 | |
|
| 0.3813 | 5.88 | 1000 | 0.4031 | |
|
| 0.3561 | 6.47 | 1100 | 0.3943 | |
|
| 0.3359 | 7.06 | 1200 | 0.3864 | |
|
| 0.3126 | 7.65 | 1300 | 0.3889 | |
|
| 0.2948 | 8.24 | 1400 | 0.3869 | |
|
| 0.2816 | 8.82 | 1500 | 0.3788 | |
|
| 0.2522 | 9.41 | 1600 | 0.3891 | |
|
| 0.2451 | 10.0 | 1700 | 0.3849 | |
|
| 0.2148 | 10.59 | 1800 | 0.3784 | |
|
| 0.2132 | 11.18 | 1900 | 0.3716 | |
|
| 0.1882 | 11.76 | 2000 | 0.3659 | |
|
| 0.1754 | 12.35 | 2100 | 0.3737 | |
|
| 0.169 | 12.94 | 2200 | 0.3711 | |
|
| 0.1559 | 13.53 | 2300 | 0.3672 | |
|
| 0.1537 | 14.12 | 2400 | 0.3391 | |
|
| 0.1427 | 14.71 | 2500 | 0.3516 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.25.1 |
|
- Pytorch 1.13.0+cu116 |
|
- Datasets 2.8.0 |
|
- Tokenizers 0.13.2 |
|
|