README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - mlner2021
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: mlner-mlwptok-muril
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: mlner2021
          type: mlner2021
          args: MLNER2021
        metrics:
          - name: Precision
            type: precision
            value: 0
          - name: Recall
            type: recall
            value: 0
          - name: F1
            type: f1
            value: 0
          - name: Accuracy
            type: accuracy
            value: 0.8112759262826688

mlner-mlwptok-muril

This model is a fine-tuned version of google/muril-base-cased on the mlner2021 dataset. It achieves the following results on the evaluation set:

• Loss: 0.8331
• Precision: 0.0
• Recall: 0.0
• F1: 0.0
• Accuracy: 0.8113

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: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
1.447	1.0	1389	0.9396	0.0	0.0	0.0	0.8113
0.898	2.0	2778	0.8883	0.0	0.0	0.0	0.8113
0.859	3.0	4167	0.8721	0.0	0.0	0.0	0.8113
0.8302	4.0	5556	0.8666	0.0	0.0	0.0	0.8113
0.8165	5.0	6945	0.8403	0.0	0.0	0.0	0.8113
0.8143	6.0	8334	0.8376	0.0	0.0	0.0	0.8113
0.8034	7.0	9723	0.8393	0.0	0.0	0.0	0.8113
0.7766	8.0	11112	0.8383	0.0	0.0	0.0	0.8113
0.794	9.0	12501	0.8346	0.0	0.0	0.0	0.8113
0.7858	10.0	13890	0.8331	0.0	0.0	0.0	0.8113

Framework versions

• Transformers 4.18.0
• Pytorch 1.10.0+cu111
• Datasets 2.0.0
• Tokenizers 0.11.6