Hugging Face's logo

nguyenanh2803
/
gg-bert-base-uncased

Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
Inference Endpoints
Model card Files Community
gg-bert-base-uncased / README.md
nguyenanh2803's picture
nguyenanh2803
Training in progress, step 500
12fbadd verified
preview code
|
raw
history blame
3.8 kB
metadata
license: mit
base_model: FacebookAI/roberta-large
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: absa-train-service-roberta-large
    results: []

Visualize in Weights & Biases Visualize in Weights & Biases

absa-train-service-roberta-large

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

  • Loss: 0.8683
  • Accuracy: 0.7424
  • Precision: 0.7345
  • Recall: 0.7367
  • F1: 0.7302

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: 0.0002
  • 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
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
2.2255 1.0 469 2.0677 0.3296 0.1937 0.3250 0.2297
1.8236 2.0 938 1.7061 0.504 0.5413 0.4914 0.4567
1.5384 3.0 1407 1.4381 0.552 0.5944 0.5549 0.5196
1.4301 4.0 1876 1.3316 0.5984 0.6000 0.5990 0.5618
1.3776 5.0 2345 1.1645 0.6576 0.6817 0.6491 0.6332
1.2078 6.0 2814 1.0967 0.6448 0.7035 0.6348 0.6110
1.2535 7.0 3283 1.0565 0.7008 0.7467 0.6967 0.7066
1.2921 8.0 3752 1.0049 0.6976 0.7013 0.6884 0.6813
1.178 9.0 4221 1.0438 0.648 0.7746 0.6423 0.6387
1.2324 10.0 4690 1.0203 0.6896 0.7096 0.6831 0.6704
1.1899 11.0 5159 1.0193 0.6864 0.7391 0.6819 0.6834
1.1515 12.0 5628 0.9722 0.6944 0.7164 0.6924 0.6860
1.1604 13.0 6097 0.9372 0.7312 0.7543 0.7311 0.7259
1.1229 14.0 6566 0.9265 0.72 0.7278 0.7139 0.7147
1.1459 15.0 7035 0.8896 0.7376 0.7264 0.7323 0.7183
1.1281 16.0 7504 0.9074 0.7152 0.7107 0.7087 0.7012
1.1794 17.0 7973 0.8914 0.7424 0.7293 0.7354 0.7266
1.1101 18.0 8442 0.8707 0.7216 0.7161 0.7141 0.7059
1.1215 19.0 8911 0.8656 0.7408 0.7322 0.7348 0.7274
1.0483 20.0 9380 0.8683 0.7424 0.7345 0.7367 0.7302

Framework versions

  • Transformers 4.43.2
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1