metadata
base_model: SALT-NLP/FLANG-BERT
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: FLANG-BERT_Synonym-wordnet
results: []
FLANG-BERT_Synonym-wordnet
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: 0.2403
- Accuracy: 0.9189
- F1: 0.9190
- Precision: 0.9194
- Recall: 0.9189
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 |
|---|---|---|---|---|---|---|---|
| 0.7933 | 1.0 | 91 | 0.7348 | 0.6880 | 0.6790 | 0.6972 | 0.6880 |
| 0.392 | 2.0 | 182 | 0.3757 | 0.8456 | 0.8461 | 0.8488 | 0.8456 |
| 0.2646 | 3.0 | 273 | 0.3044 | 0.8846 | 0.8839 | 0.8876 | 0.8846 |
| 0.1867 | 4.0 | 364 | 0.3522 | 0.8846 | 0.8846 | 0.8910 | 0.8846 |
| 0.1158 | 5.0 | 455 | 0.2403 | 0.9189 | 0.9190 | 0.9194 | 0.9189 |
| 0.1375 | 6.0 | 546 | 0.3255 | 0.9111 | 0.9105 | 0.9108 | 0.9111 |
| 0.1311 | 7.0 | 637 | 0.4090 | 0.8924 | 0.8930 | 0.9028 | 0.8924 |
| 0.1054 | 8.0 | 728 | 0.4269 | 0.9017 | 0.9015 | 0.9023 | 0.9017 |
| 0.0739 | 9.0 | 819 | 0.4098 | 0.9002 | 0.8992 | 0.9008 | 0.9002 |
| 0.0389 | 10.0 | 910 | 0.4411 | 0.9033 | 0.9030 | 0.9072 | 0.9033 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1