|
--- |
|
license: apache-2.0 |
|
base_model: bert-base-uncased |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- f1 |
|
model-index: |
|
- name: boss-sentiment-12000-bert-base-uncased |
|
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. --> |
|
|
|
# boss-sentiment-12000-bert-base-uncased |
|
|
|
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- F1: 0.7380 |
|
- Acc: 0.8773 |
|
- Loss: 0.9558 |
|
|
|
## 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: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | F1 | Acc | Validation Loss | |
|
|:-------------:|:-----:|:----:|:------:|:------:|:---------------:| |
|
| 0.929 | 1.0 | 750 | 0.6983 | 0.8609 | 0.4073 | |
|
| 0.481 | 2.0 | 1500 | 0.7179 | 0.8689 | 0.3605 | |
|
| 0.3564 | 3.0 | 2250 | 0.7269 | 0.8703 | 0.3834 | |
|
| 0.2369 | 4.0 | 3000 | 0.7006 | 0.8465 | 0.5631 | |
|
| 0.1536 | 5.0 | 3750 | 0.7237 | 0.8591 | 0.6596 | |
|
| 0.1228 | 6.0 | 4500 | 0.7285 | 0.8660 | 0.7316 | |
|
| 0.0831 | 7.0 | 5250 | 0.7454 | 0.8817 | 0.6420 | |
|
| 0.0687 | 8.0 | 6000 | 0.6955 | 0.8354 | 1.1172 | |
|
| 0.0541 | 9.0 | 6750 | 0.7143 | 0.8479 | 1.0556 | |
|
| 0.0465 | 10.0 | 7500 | 0.7473 | 0.8889 | 0.7691 | |
|
| 0.0404 | 11.0 | 8250 | 0.7209 | 0.8636 | 1.0274 | |
|
| 0.0315 | 12.0 | 9000 | 0.7082 | 0.8401 | 1.2706 | |
|
| 0.0329 | 13.0 | 9750 | 0.7380 | 0.8773 | 0.9558 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.0 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|
