You can deploy this model and start earning money today!

leomaurodesenv/
nli-MiniLM2-L6-H768-disaster-tweet-jailbreaking

Name: nli-MiniLM2-L6-H768-disaster-tweet-jailbreaking
Availability: InStock

generated_from_trainer

cross-encoder/nli-MiniLM2-L6-H768

finetune

apache-2.0

text-embeddings-inference

endpoints_compatible

Views

No views yet

nli-MiniLM2-L6-H768-disaster-tweet-jailbreaking

This model is a fine-tuned version of cross-encoder/nli-MiniLM2-L6-H768 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6495
Accuracy: 0.6536

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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5734	1.0	243	0.6503	0.6536
0.4968	2.0	486	0.7471	0.6247
0.4232	3.0	729	0.7203	0.6969
0.4009	4.0	972	1.0772	0.6309

Framework versions

Transformers 5.2.0
Pytorch 2.10.0+cu128
Datasets 4.5.0
Tokenizers 0.22.2

leomaurodesenv/nli-MiniLM2-L6-H768-disaster-tweet-jailbreaking

nli-MiniLM2-L6-H768-disaster-tweet-jailbreaking

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

leomaurodesenv/
nli-MiniLM2-L6-H768-disaster-tweet-jailbreaking