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distilroberta-rbm231k-ep20-op40-news_api_2p8k

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metadata
license: apache-2.0
base_model: judy93536/distilroberta-rbm231k-ep20-op40
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: distilroberta-rbm231k-ep20-op40-news_api_2p8k
    results: []

distilroberta-rbm231k-ep20-op40-news_api_2p8k

This model is a fine-tuned version of judy93536/distilroberta-rbm231k-ep20-op40 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3991
  • Accuracy: 0.8946

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: 2.153335054745316e-06
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.4
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 143 1.0982 0.3480
No log 2.0 286 1.0901 0.3480
No log 3.0 429 1.0754 0.3937
1.089 4.0 572 1.0446 0.4218
1.089 5.0 715 0.9983 0.4587
1.089 6.0 858 0.9316 0.5395
0.9811 7.0 1001 0.8240 0.6696
0.9811 8.0 1144 0.6669 0.7909
0.9811 9.0 1287 0.5055 0.8366
0.9811 10.0 1430 0.4123 0.8541
0.6112 11.0 1573 0.3531 0.8717
0.6112 12.0 1716 0.3399 0.8682
0.6112 13.0 1859 0.3304 0.8787
0.3218 14.0 2002 0.3270 0.8840
0.3218 15.0 2145 0.3201 0.8805
0.3218 16.0 2288 0.3276 0.8910
0.3218 17.0 2431 0.3326 0.8787
0.222 18.0 2574 0.3442 0.8928
0.222 19.0 2717 0.3456 0.8893
0.222 20.0 2860 0.3515 0.8893
0.1698 21.0 3003 0.3660 0.8893
0.1698 22.0 3146 0.3723 0.8928
0.1698 23.0 3289 0.3732 0.8928
0.1698 24.0 3432 0.3786 0.8928
0.1347 25.0 3575 0.3910 0.8963
0.1347 26.0 3718 0.3894 0.8963
0.1347 27.0 3861 0.3881 0.8981
0.1177 28.0 4004 0.3898 0.8981
0.1177 29.0 4147 0.3988 0.8946
0.1177 30.0 4290 0.3991 0.8946

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0