Edit model card

Model Card for Model ID

Thesaurus category mapping model based on Transformer architecture

Model Details

Model Description

  • Developed by: shnguo
  • Funded by [optional]: gramtech
  • Shared by [optional]: shnguo
  • Model type: classfication
  • Language(s) (NLP): English
  • License: MIT
  • Finetuned from model [optional]: distilbert

Training Details

Evaluation

  • {'eval_loss': 0.028821110725402832, 'eval_accuracy': 0.9941857972232465, 'eval_f1': 0.9940715947938238, 'eval_runtime': 54.5075, 'eval_samples_per_second': 2139.358, 'eval_steps_per_second': 66.872, 'epoch': 2.0}
  • {'train_runtime': 20346.1721, 'train_samples_per_second': 561.671, 'train_steps_per_second': 17.552, 'train_loss': 0.2077474573270054, 'epoch': 2.0}
  • wandb: \ 0.462 MB of 0.462 MB uploaded
  • wandb:
  • wandb: Run summary:
  • wandb: eval/accuracy 0.99419
  • wandb: eval/f1 0.99407
  • wandb: eval/loss 0.02882
  • wandb: eval/runtime 54.5075
  • wandb: eval/samples_per_second 2139.358
  • wandb: eval/steps_per_second 66.872
  • wandb: total_flos 3.2915880370021428e+16
  • wandb: train/epoch 2.0
  • wandb: train/global_step 357122
  • wandb: train/grad_norm 0.01881
  • wandb: train/learning_rate 0.0
  • wandb: train/loss 0.0443
  • wandb: train_loss 0.20775
  • wandb: train_runtime 20346.1721
  • wandb: train_samples_per_second 561.671
  • wandb: train_steps_per_second 17.552
  • wandb:
  • wandb: 🚀 View run feasible-voice-8 at: https://wandb.ai/shn-guo/distilbert-base-uncased-finetuned-cate/runs/lygbrbzx
  • wandb: ⭐️ View project at: https://wandb.ai/shn-guo/distilbert-base-uncased-finetuned-cate
  • wandb: Synced 6 W&B file(s), 0 media file(s), 2 artifact file(s) and 0 other file(s)
  • wandb: Find logs at: ./wandb/run-20240618_133925-lygbrbzx/logs
Downloads last month
8
Safetensors
Model size
68.1M 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.