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srmishra/
ce-MiniLM-L6layer

Name: ce-MiniLM-L6layer
Availability: InStock

generated_from_trainer

cross-encoder/ms-marco-MiniLM-L6-v2

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ce-MiniLM-L6layer

This model is a fine-tuned version of cross-encoder/ms-marco-MiniLM-L-6-v2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1559
Accuracy: 0.7273
Precision: 0.9091
Recall: 0.6349

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall
12.9679	1.0	56	20.2827	0.6970	0.7797	0.7302
9.2483	2.0	112	12.1491	0.6465	0.7188	0.7302
1.9612	3.0	168	1.7406	0.6667	0.8409	0.5873
0.5046	4.0	224	0.4060	0.6061	0.8158	0.4921
0.3575	5.0	280	0.2410	0.6667	0.7885	0.6508
0.244	6.0	336	0.1860	0.6263	0.9062	0.4603
0.2324	7.0	392	0.1706	0.6970	0.9231	0.5714
0.1958	8.0	448	0.1873	0.7172	0.7869	0.7619
0.1687	9.0	504	0.1742	0.7778	0.8868	0.7460
0.1581	10.0	560	0.1559	0.7273	0.9091	0.6349

Framework versions

Transformers 4.37.2
Pytorch 2.2.1
Datasets 2.14.6
Tokenizers 0.15.1

srmishra/ce-MiniLM-L6layer

ce-MiniLM-L6layer

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

srmishra/
ce-MiniLM-L6layer