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metadata
license: apache-2.0
library_name: peft
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
base_model: distilbert-base-uncased
model-index:
  - name: distilbert-base-uncased-tokenclassification_lora
    results: []

distilbert-base-uncased-tokenclassification_lora

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3198
  • Precision: 0.0
  • Recall: 0.0
  • F1: 0.0
  • Accuracy: 0.9213

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: 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 Precision Recall F1 Accuracy
No log 1.0 213 0.4745 0.0 0.0 0.0 0.9205
No log 2.0 426 0.4360 0.0 0.0 0.0 0.9205
0.8491 3.0 639 0.3983 0.0 0.0 0.0 0.9205
0.8491 4.0 852 0.3645 0.0 0.0 0.0 0.9205
0.2454 5.0 1065 0.3428 0.0 0.0 0.0 0.9205
0.2454 6.0 1278 0.3345 0.0 0.0 0.0 0.9208
0.2454 7.0 1491 0.3266 0.0 0.0 0.0 0.9208
0.2139 8.0 1704 0.3227 0.0 0.0 0.0 0.9210
0.2139 9.0 1917 0.3203 0.0 0.0 0.0 0.9212
0.2027 10.0 2130 0.3198 0.0 0.0 0.0 0.9213

Framework versions

  • PEFT 0.7.1
  • Transformers 4.36.2
  • Pytorch 2.0.0+cu117
  • Datasets 2.16.1
  • Tokenizers 0.15.0