README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: IKT_classifier_economywide_best
    results: []

IKT_classifier_economywide_best

This model is a fine-tuned version of sentence-transformers/all-mpnet-base-v2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1819
• Precision Weighted: 0.9628
• Precision Macro: 0.9639
• Recall Weighted: 0.9623
• Recall Samples: 0.9606
• F1-score: 0.9619
• Accuracy: 0.9623

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: 4.427532456702983e-05
• train_batch_size: 3
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 6
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100.0
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision Weighted	Precision Macro	Recall Weighted	Recall Samples	F1-score	Accuracy
No log	1.0	159	0.1640	0.9628	0.9639	0.9623	0.9606	0.9619	0.9623
No log	2.0	318	0.2042	0.9531	0.9521	0.9528	0.9533	0.9526	0.9528
No log	3.0	477	0.2298	0.9457	0.9479	0.9434	0.9402	0.9427	0.9434
0.1907	4.0	636	0.1582	0.9718	0.9723	0.9717	0.9708	0.9715	0.9717
0.1907	5.0	795	0.1819	0.9628	0.9639	0.9623	0.9606	0.9619	0.9623

Framework versions

• Transformers 4.30.2
• Pytorch 2.0.1+cu118
• Datasets 2.13.1
• Tokenizers 0.13.3