metadata

library_name: transformers
license: cc-by-4.0
base_model: l3cube-pune/indic-sentence-bert-nli
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: indic-sentence-bert-nli-profanity-mr
    results: []

indic-sentence-bert-nli-profanity-mr

This model is a fine-tuned version of l3cube-pune/indic-sentence-bert-nli on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4716
Accuracy: 0.9035
Precision: 0.4517
Recall: 0.5
F1: 0.4746

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: 32
eval_batch_size: 128
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.5063	0.9836	30	0.4867	0.8819	0.4410	0.5	0.4686
0.3827	2.0	61	0.3841	0.8819	0.4410	0.5	0.4686
0.331	2.9836	91	0.3633	0.8819	0.4410	0.5	0.4686
0.323	4.0	122	0.3648	0.8819	0.4410	0.5	0.4686
0.295	4.9836	152	0.3657	0.8819	0.4410	0.5	0.4686
0.3048	6.0	183	0.3668	0.8819	0.4410	0.5	0.4686
0.3168	6.9836	213	0.3667	0.8819	0.4410	0.5	0.4686
0.3112	8.0	244	0.3666	0.8819	0.4410	0.5	0.4686
0.2971	8.9836	274	0.3663	0.8819	0.4410	0.5	0.4686
0.3009	9.8361	300	0.3662	0.8819	0.4410	0.5	0.4686

Framework versions

Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0