metadata

language:
  - vi
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
  - generated_from_trainer
model-index:
  - name: xlm-roberta-large_baseline_syllables
    results: []

xlm-roberta-large_baseline_syllables

This model is a fine-tuned version of FacebookAI/xlm-roberta-large on the covid19_ner dataset. It achieves the following results on the evaluation set:

Loss: 0.0838
Patient Id: 0.9883
Name: 0.9409
Gender: 0.9712
Age: 0.9767
Job: 0.8506
Location: 0.9670
Organization: 0.9134
Date: 0.9860
Symptom And Disease: 0.8820
Transportation: 0.9773
F1 Macro: 0.9453
F1 Micro: 0.9587

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Patient Id	Name	Gender	Age	Job	Location	Organization	Date	Symptom And Disease	Transportation	F1 Macro	F1 Micro
0.1707	1.0	629	0.1042	0.9528	0.9227	0.8406	0.9523	0.5899	0.9308	0.8045	0.9874	0.8248	0.96	0.8766	0.9140
0.0475	2.0	1258	0.0811	0.9841	0.9372	0.9591	0.9876	0.6849	0.9350	0.8817	0.9847	0.8584	0.9831	0.9196	0.9390
0.0312	3.0	1887	0.0744	0.9856	0.9297	0.9691	0.9875	0.7554	0.9578	0.8826	0.9869	0.8648	0.9659	0.9285	0.9498
0.0196	4.0	2516	0.0808	0.9883	0.9465	0.9644	0.9835	0.8346	0.9635	0.9136	0.9856	0.8730	0.9886	0.9442	0.9565
0.0119	5.0	3145	0.0838	0.9883	0.9409	0.9712	0.9767	0.8506	0.9670	0.9134	0.9860	0.8820	0.9773	0.9453	0.9587

Framework versions

Transformers 4.41.2
Pytorch 2.1.2
Datasets 2.19.2
Tokenizers 0.19.1