|
--- |
|
library_name: transformers |
|
license: mit |
|
base_model: xlm-roberta-base |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: GPT_nyala |
|
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. --> |
|
|
|
# GPT_nyala |
|
|
|
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: 0.0000 |
|
|
|
## 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: 3e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Use OptimizerNames.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: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| No log | 1.0 | 63 | 0.0981 | |
|
| No log | 2.0 | 126 | 0.0007 | |
|
| No log | 3.0 | 189 | 0.0002 | |
|
| No log | 4.0 | 252 | 0.0006 | |
|
| No log | 5.0 | 315 | 0.0169 | |
|
| No log | 6.0 | 378 | 0.0002 | |
|
| No log | 7.0 | 441 | 0.0001 | |
|
| 0.3539 | 8.0 | 504 | 0.0002 | |
|
| 0.3539 | 9.0 | 567 | 0.0001 | |
|
| 0.3539 | 10.0 | 630 | 0.0001 | |
|
| 0.3539 | 11.0 | 693 | 0.0001 | |
|
| 0.3539 | 12.0 | 756 | 0.0001 | |
|
| 0.3539 | 13.0 | 819 | 0.0001 | |
|
| 0.3539 | 14.0 | 882 | 0.0001 | |
|
| 0.3539 | 15.0 | 945 | 0.0001 | |
|
| 0.0012 | 16.0 | 1008 | 0.0000 | |
|
| 0.0012 | 17.0 | 1071 | 0.0001 | |
|
| 0.0012 | 18.0 | 1134 | 0.0000 | |
|
| 0.0012 | 19.0 | 1197 | 0.0000 | |
|
| 0.0012 | 20.0 | 1260 | 0.0000 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.47.1 |
|
- Pytorch 2.5.1+cu124 |
|
- Tokenizers 0.21.0 |
|
|