jb2k_bert-base-multilingual-cased-language-detection-finetuned-lora-tweet_eval_hate

This model is a fine-tuned version of jb2k/bert-base-multilingual-cased-language-detection on the tweet_eval dataset. It achieves the following results on the evaluation set:

• accuracy: 0.682

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: 0.0004
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4

Training results

accuracy	train_loss	epoch
0.573	None	0
0.676	0.6360	0
0.686	0.5747	1
0.663	0.5399	2
0.682	0.5196	3

Framework versions

• PEFT 0.8.2
• Transformers 4.37.2
• Pytorch 2.2.0
• Datasets 2.16.1
• Tokenizers 0.15.2