metadata
library_name: transformers
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: euk_roberta_large_essentiality_Network
results: []
euk_roberta_large_essentiality_Network
This model is a fine-tuned version of roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4307
- Accuracy: 0.8210
- Precision: 0.7886
- Recall: 0.8771
- F1: 0.8305
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: 1e-05
- train_batch_size: 60
- eval_batch_size: 60
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 240
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 47 | 0.5793 | 0.7023 | 0.7021 | 0.7031 | 0.7026 |
| No log | 2.0 | 94 | 0.4761 | 0.7812 | 0.7861 | 0.7727 | 0.7794 |
| No log | 3.0 | 141 | 0.4792 | 0.7769 | 0.7506 | 0.8295 | 0.7881 |
| No log | 4.0 | 188 | 0.4617 | 0.7822 | 0.7641 | 0.8168 | 0.7896 |
| No log | 5.0 | 235 | 0.4748 | 0.7769 | 0.7393 | 0.8558 | 0.7933 |
| No log | 6.0 | 282 | 0.4401 | 0.7961 | 0.7773 | 0.8303 | 0.8029 |
| No log | 7.0 | 329 | 0.4273 | 0.7968 | 0.7828 | 0.8217 | 0.8018 |
| No log | 8.0 | 376 | 0.4282 | 0.8099 | 0.7825 | 0.8587 | 0.8188 |
| No log | 9.0 | 423 | 0.4242 | 0.8099 | 0.8 | 0.8267 | 0.8131 |
| No log | 10.0 | 470 | 0.4248 | 0.8089 | 0.7908 | 0.8402 | 0.8147 |
| 1.8645 | 11.0 | 517 | 0.4183 | 0.8139 | 0.8095 | 0.8210 | 0.8152 |
| 1.8645 | 12.0 | 564 | 0.4206 | 0.8195 | 0.7988 | 0.8544 | 0.8257 |
| 1.8645 | 13.0 | 611 | 0.4225 | 0.8178 | 0.7985 | 0.8501 | 0.8235 |
| 1.8645 | 14.0 | 658 | 0.4307 | 0.8210 | 0.7886 | 0.8771 | 0.8305 |
| 1.8645 | 15.0 | 705 | 0.4259 | 0.8163 | 0.8016 | 0.8409 | 0.8208 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.9.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2