Edit model card

distilroberta-tcfd-disclosure

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

  • Loss: 1.8681

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: 8
  • seed: 42
  • gradient_accumulation_steps: 5
  • total_train_batch_size: 80
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
No log 1.0 5 2.3837
2.3918 2.0 10 2.3787
2.3918 3.0 15 2.3704
2.3754 4.0 20 2.3623
2.3754 5.0 25 2.3396
2.2976 6.0 30 2.2599
2.2976 7.0 35 2.1095
2.0439 8.0 40 2.0184
2.0439 9.0 45 1.9059
1.6799 10.0 50 1.8469
1.6799 11.0 55 1.8089
1.2948 12.0 60 1.7263
1.2948 13.0 65 1.7250
0.9621 14.0 70 1.8106
0.9621 15.0 75 1.8073
0.7356 16.0 80 1.8681

Framework versions

  • Transformers 4.28.1
  • Pytorch 2.0.0+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3
Downloads last month
26
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 rexarski/distilroberta-tcfd-disclosure

Finetuned
(525)
this model

Dataset used to train rexarski/distilroberta-tcfd-disclosure

Space using rexarski/distilroberta-tcfd-disclosure 1