e5_finetuned

This model is a fine-tuned version of intfloat/multilingual-e5-small on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0611
• Precision: 0.9494
• Recall: 0.8860
• F1: 0.9166
• Accuracy: 0.9799

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: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	0.0009	2	0.7141	0.125	1.0	0.2222	0.125
0.1046	0.9998	2334	0.0905	0.9564	0.8239	0.8852	0.9733
0.0786	2.0	4669	0.0734	0.9550	0.8540	0.9016	0.9767
0.0761	2.9998	7003	0.0690	0.9358	0.8834	0.9088	0.9778
0.0673	4.0	9338	0.0621	0.9594	0.8750	0.9152	0.9797
0.0709	4.9989	11670	0.0611	0.9494	0.8860	0.9166	0.9799

Framework versions

• Transformers 4.44.0
• Pytorch 2.1.0+cu118
• Datasets 2.20.0
• Tokenizers 0.19.1