STS-conventional-Fine-Tuning-Capstone-roberta-base-filtered-170

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

  • Loss: 2.3403
  • Accuracy: 0.7285

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: 3e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 113 0.7529 0.6816
No log 2.0 226 0.7985 0.7097
No log 3.0 339 0.8245 0.7097
No log 4.0 452 0.8816 0.6798
0.5011 5.0 565 1.0854 0.6929
0.5011 6.0 678 1.1921 0.7135
0.5011 7.0 791 1.3839 0.7228
0.5011 8.0 904 1.4560 0.7247
0.1649 9.0 1017 1.6387 0.7191
0.1649 10.0 1130 1.8012 0.7172
0.1649 11.0 1243 1.8790 0.7247
0.1649 12.0 1356 2.0223 0.7116
0.1649 13.0 1469 2.0297 0.7228
0.0639 14.0 1582 2.1202 0.7228
0.0639 15.0 1695 2.2489 0.7303
0.0639 16.0 1808 2.2505 0.7266
0.0639 17.0 1921 2.2693 0.7303
0.0198 18.0 2034 2.3216 0.7228
0.0198 19.0 2147 2.3244 0.7247
0.0198 20.0 2260 2.3403 0.7285

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
Downloads last month
26
Safetensors
Model size
125M 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 rajevan123/STS-conventional-Fine-Tuning-Capstone-roberta-base-filtered-170

Finetuned
(1374)
this model