metadata
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: rtmex23-pol4-cardif
results: []
rtmex23-pol4-cardif
This model is a fine-tuned version of cardiffnlp/twitter-xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6787
- F1: 0.8463
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_steps: 500
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.7006 | 1.0 | 17996 | 0.6293 | 0.6758 |
| 0.5558 | 2.0 | 35992 | 0.5515 | 0.7590 |
| 0.4566 | 3.0 | 53988 | 0.5066 | 0.7939 |
| 0.3855 | 4.0 | 71984 | 0.4959 | 0.8217 |
| 0.3258 | 5.0 | 89980 | 0.5075 | 0.8200 |
| 0.2744 | 6.0 | 107976 | 0.5251 | 0.8409 |
| 0.2322 | 7.0 | 125972 | 0.5889 | 0.8461 |
| 0.2029 | 8.0 | 143968 | 0.6787 | 0.8463 |
Framework versions
- Transformers 4.29.1
- Pytorch 1.13.1
- Datasets 2.12.0
- Tokenizers 0.13.3