Edit model card

distilbert-base-multilingual-cased-on-custom-kural-500

This model is a fine-tuned version of distilbert-base-multilingual-cased on the custom 500 kural dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4608
  • Accuracy: 0.91

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
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 25 0.2557 0.89
No log 2.0 50 0.5950 0.79
No log 3.0 75 0.1989 0.92
No log 4.0 100 0.4856 0.89
No log 5.0 125 0.4785 0.89
No log 6.0 150 0.4426 0.91
No log 7.0 175 0.4699 0.9
No log 8.0 200 0.4488 0.92
No log 9.0 225 0.4552 0.92
No log 10.0 250 0.4608 0.91

Framework versions

  • Transformers 4.39.2
  • Pytorch 2.1.2
  • Datasets 2.1.0
  • Tokenizers 0.15.2
Downloads last month
4
Safetensors
Model size
135M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for bikram22pi7/distilbert-base-multilingual-cased-on-custom-kural-500

Finetuned
(191)
this model