README.md

metadata

license: mit
base_model: xlm-roberta-large
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: xlm-roberta-large-twitter-indonesia-sarcastic
    results: []

xlm-roberta-large-twitter-indonesia-sarcastic

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

• Loss: 0.4322
• Accuracy: 0.8885
• F1: 0.7692
• Precision: 0.7937
• Recall: 0.7463

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: 1e-05
• train_batch_size: 32
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• num_epochs: 100.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.5862	1.0	59	0.5304	0.75	0.0	0.0	0.0
0.5168	2.0	118	0.4897	0.75	0.0	0.0	0.0
0.4771	3.0	177	0.4535	0.7948	0.3373	0.875	0.2090
0.4101	4.0	236	0.4235	0.7910	0.6585	0.5567	0.8060
0.3225	5.0	295	0.4733	0.8507	0.5918	0.9355	0.4328
0.2246	6.0	354	0.3362	0.8694	0.7009	0.82	0.6119
0.166	7.0	413	0.3672	0.8769	0.7227	0.8269	0.6418
0.0989	8.0	472	0.3835	0.8769	0.7626	0.7361	0.7910
0.0797	9.0	531	0.4379	0.8993	0.7939	0.8125	0.7761
0.08	10.0	590	0.7677	0.8545	0.7451	0.6628	0.8507
0.0505	11.0	649	0.7316	0.8806	0.7288	0.8431	0.6418
0.073	12.0	708	0.4796	0.9104	0.8182	0.8308	0.8060
0.05	13.0	767	0.8469	0.8694	0.7059	0.8077	0.6269
0.0583	14.0	826	0.7266	0.8918	0.7563	0.8654	0.6716
0.0275	15.0	885	0.8974	0.8918	0.7387	0.9318	0.6119

Framework versions

• Transformers 4.36.2
• Pytorch 2.1.1+cu121
• Datasets 2.15.0
• Tokenizers 0.15.0