README.md

metadata

license: mit
base_model: roberta-large
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: test-NERv3
    results: []

test-NERv3

This model is a fine-tuned version of roberta-large on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.1950
• Precision: 0.0009
• Recall: 0.0026
• F1: 0.0014
• Accuracy: 0.1510

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: 16
• 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: 500
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
2.2261	1.0	14	2.1950	0.0009	0.0026	0.0014	0.1510

Framework versions

• Transformers 4.34.0
• Pytorch 2.0.1+cu117
• Datasets 2.12.0
• Tokenizers 0.14.1