scenario-TCR-4_data-cardiffnlp_tweet_sentiment_multilingual_all

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

• Loss: 1.2568
• Accuracy: 0.6258
• F1: 0.6220

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: 32
• eval_batch_size: 32
• seed: 48
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 500

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
1.0005	1.09	500	0.9616	0.5517	0.5238
0.8578	2.17	1000	0.8651	0.5968	0.5750
0.7545	3.26	1500	0.9179	0.6269	0.6224
0.6418	4.35	2000	0.9266	0.6169	0.6117
0.5162	5.43	2500	1.0184	0.6331	0.6298
0.4188	6.52	3000	1.1995	0.6080	0.6075
0.3517	7.61	3500	1.2092	0.6273	0.6260
0.2947	8.7	4000	1.2915	0.6177	0.6171
0.2488	9.78	4500	1.3765	0.6219	0.6210
0.2152	10.87	5000	1.2568	0.6258	0.6220

Framework versions

• Transformers 4.33.3
• Pytorch 2.1.1+cu121
• Datasets 2.14.5
• Tokenizers 0.13.3