|
--- |
|
base_model: klue/roberta-small |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: binary_every_exp |
|
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. --> |
|
|
|
# binary_every_exp |
|
|
|
This model is a fine-tuned version of [klue/roberta-small](https://huggingface.co/klue/roberta-small) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0015 |
|
- Precision: 1.0 |
|
- Recall: 1.0 |
|
- F1: 1.0 |
|
- Accuracy: 1.0 |
|
|
|
## 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: 64 |
|
- eval_batch_size: 64 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 8 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| No log | 1.0 | 9 | 0.0149 | 1.0 | 1.0 | 1.0 | 1.0 | |
|
| No log | 2.0 | 18 | 0.0043 | 1.0 | 1.0 | 1.0 | 1.0 | |
|
| No log | 3.0 | 27 | 0.0344 | 0.9444 | 1.0 | 0.9714 | 0.9808 | |
|
| No log | 4.0 | 36 | 0.0042 | 1.0 | 1.0 | 1.0 | 1.0 | |
|
| No log | 5.0 | 45 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 | |
|
| No log | 6.0 | 54 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 | |
|
| No log | 7.0 | 63 | 0.0017 | 1.0 | 1.0 | 1.0 | 1.0 | |
|
| No log | 8.0 | 72 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.42.3 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.19.1 |
|
|
