metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: citation_intent_classification_roberta_dapt
results: []
citation_intent_classification_roberta_dapt
This model is a fine-tuned version of ltuzova/cs_domain_pretrained_model on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5175
- Accuracy: 0.5108
- F1 Macro: 0.1127
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: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|---|---|---|---|---|---|
| 1.6621 | 1.0 | 105 | 1.5071 | 0.5175 | 0.1137 |
| 1.4561 | 2.0 | 211 | 1.3867 | 0.5175 | 0.1137 |
| 1.4054 | 3.0 | 316 | 1.3482 | 0.5175 | 0.1137 |
| 1.3753 | 4.0 | 422 | 1.3319 | 0.5175 | 0.1137 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.13.1+cu117
- Datasets 2.13.2
- Tokenizers 0.13.3