finetune_output / README.md
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metadata
license: mit
base_model: roberta-base
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: finetune_output
    results: []
datasets:
  - surrey-nlp/PLOD-CW
language:
  - en
library_name: transformers

finetune_output

This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1540
  • Precision: 0.9636
  • Recall: 0.9510
  • F1: 0.9573
  • Accuracy: 0.952

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.3726 0.75 100 0.1531 0.9551 0.9467 0.9509 0.946
0.1662 1.49 200 0.1540 0.9636 0.9510 0.9573 0.952

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.0.1+cu117
  • Datasets 2.12.0
  • Tokenizers 0.13.2