|
|
--- |
|
|
license: apache-2.0 |
|
|
base_model: distilbert/distilbert-base-uncased-finetuned-sst-2-english |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: sucidal-text-classification-distillbert |
|
|
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. --> |
|
|
|
|
|
# sucidal-text-classification-distillbert |
|
|
|
|
|
This model is a fine-tuned version of [distilbert/distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert/distilbert-base-uncased-finetuned-sst-2-english) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.4590 |
|
|
- Accuracy: 0.8198 |
|
|
- F1 Score: 0.8198 |
|
|
|
|
|
## 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: 16 |
|
|
- eval_batch_size: 16 |
|
|
- seed: 42 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- lr_scheduler_warmup_steps: 500 |
|
|
- num_epochs: 3 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | |
|
|
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:| |
|
|
| 0.3602 | 0.1885 | 500 | 0.7867 | 0.7670 | 0.7670 | |
|
|
| 0.6285 | 0.3769 | 1000 | 0.5574 | 0.7795 | 0.7795 | |
|
|
| 0.5624 | 0.5654 | 1500 | 0.5011 | 0.7988 | 0.7988 | |
|
|
| 0.5413 | 0.7539 | 2000 | 0.4968 | 0.8017 | 0.8017 | |
|
|
| 0.5084 | 0.9423 | 2500 | 0.4712 | 0.8085 | 0.8085 | |
|
|
| 0.4253 | 1.1308 | 3000 | 0.4938 | 0.8053 | 0.8053 | |
|
|
| 0.3915 | 1.3193 | 3500 | 0.4781 | 0.8136 | 0.8136 | |
|
|
| 0.3739 | 1.5077 | 4000 | 0.5195 | 0.8043 | 0.8043 | |
|
|
| 0.3638 | 1.6962 | 4500 | 0.4790 | 0.8201 | 0.8201 | |
|
|
| 0.3667 | 1.8847 | 5000 | 0.4590 | 0.8198 | 0.8198 | |
|
|
| 0.3182 | 2.0731 | 5500 | 0.5129 | 0.8218 | 0.8218 | |
|
|
| 0.2325 | 2.2616 | 6000 | 0.5279 | 0.8198 | 0.8198 | |
|
|
| 0.2318 | 2.4501 | 6500 | 0.5368 | 0.8197 | 0.8197 | |
|
|
| 0.2219 | 2.6385 | 7000 | 0.5606 | 0.8221 | 0.8221 | |
|
|
| 0.2261 | 2.8270 | 7500 | 0.5406 | 0.8229 | 0.8229 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.41.2 |
|
|
- Pytorch 2.3.0+cu121 |
|
|
- Datasets 2.20.0 |
|
|
- Tokenizers 0.19.1 |
|
|
|
