This model is a fine-tuned version of microsoft/mdeberta-v3-base on the tweet_sentiment_multilingual dataset. It achieves the following results on the evaluation set:

Loss: 2.0269
Accuracy: 0.6362
F1: 0.6387

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: 66
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.8991	1.09	500	0.8258	0.6265	0.6117
0.6873	2.17	1000	0.8627	0.6481	0.6502
0.5102	3.26	1500	0.9726	0.6516	0.6440
0.3825	4.35	2000	1.1881	0.6578	0.6540
0.2946	5.43	2500	1.2475	0.6532	0.6554
0.228	6.52	3000	1.5294	0.6435	0.6458
0.2006	7.61	3500	1.6058	0.6389	0.6342
0.159	8.7	4000	1.5956	0.6528	0.6510
0.1334	9.78	4500	1.8463	0.6478	0.6409
0.1052	10.87	5000	2.0269	0.6362	0.6387

Framework versions

Transformers 4.33.3
Pytorch 2.1.1+cu121
Datasets 2.14.5
Tokenizers 0.13.3

haryoaw/scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all

scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

haryoaw/
scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all