|
--- |
|
library_name: transformers |
|
license: mit |
|
base_model: MoritzLaurer/mDeBERTa-v3-base-mnli-xnli |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: cs221-mDeBERTa-v3-base-mnli-xnli-finetuned-20-epochs |
|
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. --> |
|
|
|
# cs221-mDeBERTa-v3-base-mnli-xnli-finetuned-20-epochs |
|
|
|
This model is a fine-tuned version of [MoritzLaurer/mDeBERTa-v3-base-mnli-xnli](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-mnli-xnli) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5558 |
|
- F1: 0.7088 |
|
- Roc Auc: 0.7803 |
|
- Accuracy: 0.3953 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_steps: 100 |
|
- num_epochs: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
|
| 0.6081 | 1.0 | 64 | 0.5854 | 0.4511 | 0.6250 | 0.1759 | |
|
| 0.5318 | 2.0 | 128 | 0.5056 | 0.5413 | 0.6739 | 0.2905 | |
|
| 0.4634 | 3.0 | 192 | 0.4846 | 0.6178 | 0.7158 | 0.3103 | |
|
| 0.417 | 4.0 | 256 | 0.4696 | 0.6609 | 0.7452 | 0.3340 | |
|
| 0.3762 | 5.0 | 320 | 0.4645 | 0.6707 | 0.7522 | 0.3577 | |
|
| 0.3187 | 6.0 | 384 | 0.4622 | 0.6802 | 0.7591 | 0.3636 | |
|
| 0.2801 | 7.0 | 448 | 0.4691 | 0.6953 | 0.7702 | 0.3557 | |
|
| 0.2593 | 8.0 | 512 | 0.4847 | 0.6833 | 0.7614 | 0.3498 | |
|
| 0.2278 | 9.0 | 576 | 0.4878 | 0.6941 | 0.7691 | 0.3775 | |
|
| 0.1917 | 10.0 | 640 | 0.5014 | 0.7001 | 0.7735 | 0.3834 | |
|
| 0.1761 | 11.0 | 704 | 0.5298 | 0.7020 | 0.7747 | 0.3893 | |
|
| 0.1494 | 12.0 | 768 | 0.5417 | 0.7009 | 0.7741 | 0.3972 | |
|
| 0.1422 | 13.0 | 832 | 0.5437 | 0.7074 | 0.7791 | 0.3953 | |
|
| 0.1132 | 14.0 | 896 | 0.5602 | 0.6965 | 0.7709 | 0.3794 | |
|
| 0.108 | 15.0 | 960 | 0.5558 | 0.7088 | 0.7803 | 0.3953 | |
|
| 0.0945 | 16.0 | 1024 | 0.5700 | 0.7026 | 0.7753 | 0.3913 | |
|
| 0.1004 | 17.0 | 1088 | 0.5748 | 0.7055 | 0.7776 | 0.3953 | |
|
| 0.0857 | 18.0 | 1152 | 0.5733 | 0.7056 | 0.7776 | 0.3913 | |
|
| 0.0893 | 19.0 | 1216 | 0.5731 | 0.7032 | 0.7759 | 0.3913 | |
|
| 0.0881 | 20.0 | 1280 | 0.5735 | 0.7040 | 0.7765 | 0.3913 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.47.1 |
|
- Pytorch 2.5.1+cu121 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.21.0 |
|
|
