|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: bert-base-uncased |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- sem_eval_2018_task_1 |
|
metrics: |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: bert-finetuned-sem_eval-english |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: sem_eval_2018_task_1 |
|
type: sem_eval_2018_task_1 |
|
config: subtask5.english |
|
split: validation |
|
args: subtask5.english |
|
metrics: |
|
- name: F1 |
|
type: f1 |
|
value: 0.7071713147410359 |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.2866817155756208 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# bert-finetuned-sem_eval-english |
|
|
|
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the sem_eval_2018_task_1 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3063 |
|
- F1: 0.7072 |
|
- Roc Auc: 0.7999 |
|
- Accuracy: 0.2867 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- 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: 5 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
|
| No log | 1.0 | 428 | 0.3278 | 0.6765 | 0.7759 | 0.2641 | |
|
| 0.3858 | 2.0 | 856 | 0.3032 | 0.6879 | 0.7804 | 0.2743 | |
|
| 0.2836 | 3.0 | 1284 | 0.3017 | 0.7033 | 0.7957 | 0.2935 | |
|
| 0.2446 | 4.0 | 1712 | 0.3060 | 0.7037 | 0.7970 | 0.2799 | |
|
| 0.2225 | 5.0 | 2140 | 0.3063 | 0.7072 | 0.7999 | 0.2867 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.46.1 |
|
- Pytorch 2.5.1 |
|
- Datasets 3.1.0 |
|
- Tokenizers 0.20.1 |
|
|
