|
|
--- |
|
|
library_name: transformers |
|
|
license: mit |
|
|
base_model: roberta-large |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: roberta-largemhr2004-atomic.anion.train.no1e-06-128 |
|
|
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. --> |
|
|
|
|
|
# roberta-largemhr2004-atomic.anion.train.no1e-06-128 |
|
|
|
|
|
This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.3645 |
|
|
|
|
|
## 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: 1e-06 |
|
|
- train_batch_size: 512 |
|
|
- eval_batch_size: 1024 |
|
|
- 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: linear |
|
|
- num_epochs: 30 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|
|:-------------:|:-----:|:-----:|:---------------:| |
|
|
| 0.6351 | 1.0 | 576 | 0.4929 | |
|
|
| 0.4755 | 2.0 | 1152 | 0.4313 | |
|
|
| 0.4406 | 3.0 | 1728 | 0.4136 | |
|
|
| 0.4208 | 4.0 | 2304 | 0.4072 | |
|
|
| 0.4089 | 5.0 | 2880 | 0.3982 | |
|
|
| 0.3989 | 6.0 | 3456 | 0.3869 | |
|
|
| 0.3913 | 7.0 | 4032 | 0.3837 | |
|
|
| 0.3836 | 8.0 | 4608 | 0.3793 | |
|
|
| 0.3766 | 9.0 | 5184 | 0.3793 | |
|
|
| 0.3715 | 10.0 | 5760 | 0.3754 | |
|
|
| 0.3669 | 11.0 | 6336 | 0.3726 | |
|
|
| 0.3653 | 12.0 | 6912 | 0.3681 | |
|
|
| 0.3594 | 13.0 | 7488 | 0.3697 | |
|
|
| 0.3534 | 14.0 | 8064 | 0.3725 | |
|
|
| 0.353 | 15.0 | 8640 | 0.3678 | |
|
|
| 0.3509 | 16.0 | 9216 | 0.3651 | |
|
|
| 0.3474 | 17.0 | 9792 | 0.3635 | |
|
|
| 0.3467 | 18.0 | 10368 | 0.3676 | |
|
|
| 0.3428 | 19.0 | 10944 | 0.3631 | |
|
|
| 0.3408 | 20.0 | 11520 | 0.3668 | |
|
|
| 0.3373 | 21.0 | 12096 | 0.3645 | |
|
|
| 0.3397 | 22.0 | 12672 | 0.3645 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.51.2 |
|
|
- Pytorch 2.6.0+cu124 |
|
|
- Datasets 3.5.0 |
|
|
- Tokenizers 0.21.1 |
|
|
|
