metadata
base_model: ''
tags:
- generated_from_trainer
datasets:
- few-nerd
model-index:
- name: span-marker-bert-base-fewnerd-coarse-super
results: []
span-marker-bert-base-fewnerd-coarse-super
This model is a fine-tuned version of on the few-nerd dataset. It achieves the following results on the evaluation set:
- Loss: 0.0191
- Overall Precision: 0.7817
- Overall Recall: 0.7683
- Overall F1: 0.7749
- Overall Accuracy: 0.9394
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0393 | 0.16 | 200 | 0.0348 | 0.7084 | 0.6377 | 0.6712 | 0.9082 |
| 0.0311 | 0.33 | 400 | 0.0233 | 0.7744 | 0.6994 | 0.7350 | 0.9225 |
| 0.0242 | 0.49 | 600 | 0.0214 | 0.7725 | 0.7293 | 0.7503 | 0.9323 |
| 0.0238 | 0.65 | 800 | 0.0204 | 0.7744 | 0.7663 | 0.7703 | 0.9359 |
| 0.0212 | 0.81 | 1000 | 0.0193 | 0.7878 | 0.7617 | 0.7746 | 0.9379 |
| 0.0181 | 0.98 | 1200 | 0.0190 | 0.7830 | 0.7671 | 0.7750 | 0.9391 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3