Edit model card

led-risalah_data_v9

This model is a fine-tuned version of silmi224/finetune-led-35000 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6418
  • Rouge1 Precision: 0.6262
  • Rouge1 Recall: 0.3099
  • Rouge1 Fmeasure: 0.4143

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: 1
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Precision Rouge1 Recall Rouge1 Fmeasure
1.2018 0.9714 17 1.4789 0.5782 0.2807 0.3761
1.0123 2.0 35 1.4305 0.5931 0.2892 0.3876
0.8845 2.9714 52 1.4693 0.6327 0.3088 0.4148
0.705 4.0 70 1.4903 0.6263 0.3052 0.4096
0.6323 4.9714 87 1.5086 0.6167 0.3052 0.4075
0.5926 6.0 105 1.5386 0.6238 0.3031 0.4072
0.5149 6.9714 122 1.5742 0.6308 0.3035 0.4096
0.4324 8.0 140 1.6112 0.6188 0.3083 0.411
0.3748 8.9714 157 1.6382 0.6262 0.3097 0.4138
0.4033 9.7143 170 1.6418 0.6262 0.3099 0.4143

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.1.2
  • Datasets 2.19.2
  • Tokenizers 0.19.1
Downloads last month
8
Safetensors
Model size
162M 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 silmi224/led-risalah_data_v9

Finetuned
(15)
this model