|
--- |
|
license: mit |
|
base_model: camembert-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: FRA_party_tweets_climate |
|
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. --> |
|
|
|
# FRA_party_tweets_climate |
|
|
|
This model is a fine-tuned version of [camembert-base](https://huggingface.co./camembert-base) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0826 |
|
- Accuracy: 0.9857 |
|
- F1 Macro: 0.9853 |
|
- Accuracy Balanced: 0.9847 |
|
- F1 Micro: 0.9857 |
|
- Precision Macro: 0.9858 |
|
- Recall Macro: 0.9847 |
|
- Precision Micro: 0.9857 |
|
- Recall Micro: 0.9857 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 80 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.06 |
|
- num_epochs: 5 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Accuracy Balanced | F1 Micro | Precision Macro | Recall Macro | Precision Micro | Recall Micro | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:| |
|
| 0.2428 | 1.0 | 628 | 0.0792 | 0.9841 | 0.9836 | 0.9831 | 0.9841 | 0.9842 | 0.9831 | 0.9841 | 0.9841 | |
|
| 0.058 | 2.0 | 1256 | 0.0925 | 0.9809 | 0.9804 | 0.9804 | 0.9809 | 0.9804 | 0.9804 | 0.9809 | 0.9809 | |
|
| 0.0429 | 3.0 | 1884 | 0.0785 | 0.9857 | 0.9852 | 0.9846 | 0.9857 | 0.9859 | 0.9846 | 0.9857 | 0.9857 | |
|
| 0.024 | 4.0 | 2512 | 0.0829 | 0.9857 | 0.9853 | 0.9847 | 0.9857 | 0.9858 | 0.9847 | 0.9857 | 0.9857 | |
|
| 0.0202 | 5.0 | 3140 | 0.0826 | 0.9857 | 0.9853 | 0.9847 | 0.9857 | 0.9858 | 0.9847 | 0.9857 | 0.9857 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.1+cu121 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|
