|
--- |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: covid-twitter-bert-v2-no_description-stance-loss-hyp-unprocess2 |
|
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. --> |
|
|
|
# covid-twitter-bert-v2-no_description-stance-loss-hyp-unprocess2 |
|
|
|
This model is a fine-tuned version of [digitalepidemiologylab/covid-twitter-bert-v2](https://huggingface.co/digitalepidemiologylab/covid-twitter-bert-v2) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5816 |
|
- Accuracy: 0.0901 |
|
|
|
## 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: 1.4275469935864394e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 40 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 4 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.8511 | 1.0 | 700 | 0.6372 | 0.1478 | |
|
| 0.6146 | 2.0 | 1400 | 0.5816 | 0.0901 | |
|
| 0.365 | 3.0 | 2100 | 0.6170 | 0.0749 | |
|
| 0.2686 | 4.0 | 2800 | 0.7259 | 0.0688 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.19.2 |
|
- Pytorch 1.11.0+cu102 |
|
- Datasets 2.2.1 |
|
- Tokenizers 0.12.1 |
|
|
