README.md

metadata

tags:
  - generated_from_trainer
base_model: sentence-transformers/multi-qa-MiniLM-L6-cos-v1
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: all_keywords_multi-qa-MiniLM-L6-cos-v1_another
    results: []

all_keywords_multi-qa-MiniLM-L6-cos-v1_another

This model is a fine-tuned version of sentence-transformers/multi-qa-MiniLM-L6-cos-v1 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 3.2408
• Accuracy: 0.5259
• Precision: 0.5259
• Recall: 0.5259
• F1: 0.5259

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: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
2.3237	1.0	712	1.9365	0.4123	0.4123	0.4123	0.4123
2.0274	2.0	1424	1.8781	0.4502	0.4502	0.4502	0.4502
1.7498	3.0	2136	1.7664	0.4656	0.4656	0.4656	0.4656
1.6009	4.0	2848	1.7801	0.4656	0.4656	0.4656	0.4656
1.2981	5.0	3560	1.9004	0.4600	0.4600	0.4600	0.4600
1.0895	6.0	4272	2.0621	0.4642	0.4642	0.4642	0.4642
0.9878	7.0	4984	2.4640	0.4572	0.4572	0.4572	0.4572
0.784	8.0	5696	2.5635	0.5091	0.5091	0.5091	0.5091
0.6569	9.0	6408	2.5690	0.5273	0.5273	0.5273	0.5273
0.5847	10.0	7120	2.9342	0.5063	0.5063	0.5063	0.5063
0.5107	11.0	7832	2.9652	0.5091	0.5091	0.5091	0.5091
0.4954	12.0	8544	3.1480	0.5161	0.5161	0.5161	0.5161
0.4274	13.0	9256	3.2199	0.4993	0.4993	0.4993	0.4993
0.433	14.0	9968	3.2185	0.5217	0.5217	0.5217	0.5217
0.3615	15.0	10680	3.2408	0.5259	0.5259	0.5259	0.5259

Framework versions

• Transformers 4.39.3
• Pytorch 2.2.1+cu118
• Datasets 2.14.7
• Tokenizers 0.15.2