metadata
base_model: SALT-NLP/FLANG-BERT
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: FLANG-BERT_roberta-base
results: []
FLANG-BERT_roberta-base
This model is a fine-tuned version of SALT-NLP/FLANG-BERT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5101
- Accuracy: 0.8643
- F1: 0.8637
- Precision: 0.8638
- Recall: 0.8643
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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.841 | 1.0 | 91 | 0.7542 | 0.6895 | 0.6505 | 0.7281 | 0.6895 |
| 0.4766 | 2.0 | 182 | 0.4469 | 0.8159 | 0.8161 | 0.8201 | 0.8159 |
| 0.3539 | 3.0 | 273 | 0.3916 | 0.8456 | 0.8459 | 0.8473 | 0.8456 |
| 0.2452 | 4.0 | 364 | 0.4667 | 0.8362 | 0.8348 | 0.8369 | 0.8362 |
| 0.1646 | 5.0 | 455 | 0.4408 | 0.8643 | 0.8636 | 0.8643 | 0.8643 |
| 0.1273 | 6.0 | 546 | 0.5101 | 0.8643 | 0.8637 | 0.8638 | 0.8643 |
| 0.1052 | 7.0 | 637 | 0.7249 | 0.8393 | 0.8369 | 0.8413 | 0.8393 |
| 0.0889 | 8.0 | 728 | 0.5791 | 0.8424 | 0.8413 | 0.8419 | 0.8424 |
| 0.0846 | 9.0 | 819 | 0.5522 | 0.8580 | 0.8576 | 0.8577 | 0.8580 |
| 0.0764 | 10.0 | 910 | 0.7277 | 0.8549 | 0.8549 | 0.8555 | 0.8549 |
| 0.1531 | 11.0 | 1001 | 0.6068 | 0.8424 | 0.8407 | 0.8441 | 0.8424 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1