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distilroberta-rbm231k-ep20-op40-phr2

Text Classification
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Safetensors
roberta
Generated from Trainer
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metadata
license: apache-2.0
base_model: judy93536/distilroberta-rbm231k-ep20-op40
tags:
  - generated_from_trainer
datasets:
  - financial_phrasebank
metrics:
  - accuracy
model-index:
  - name: distilroberta-rbm231k-ep20-op40-phr2
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: financial_phrasebank
          type: financial_phrasebank
          config: sentences_allagree
          split: train
          args: sentences_allagree
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9558498896247241

distilroberta-rbm231k-ep20-op40-phr2

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

  • Loss: 0.1510
  • Accuracy: 0.9558

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: 1.153335054745316e-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 1.0 114 1.0772 0.5320
No log 2.0 228 1.0494 0.6159
No log 3.0 342 0.9975 0.6181
No log 4.0 456 0.9147 0.6181
1.0398 5.0 570 0.8565 0.6181
1.0398 6.0 684 0.8305 0.6181
1.0398 7.0 798 0.7759 0.6181
1.0398 8.0 912 0.7302 0.6490
0.8173 9.0 1026 0.6873 0.6865
0.8173 10.0 1140 0.6445 0.7174
0.8173 11.0 1254 0.6036 0.7439
0.8173 12.0 1368 0.5528 0.7550
0.8173 13.0 1482 0.5247 0.7550
0.5972 14.0 1596 0.4776 0.7572
0.5972 15.0 1710 0.4430 0.7616
0.5972 16.0 1824 0.3948 0.7704
0.5972 17.0 1938 0.3418 0.8455
0.4037 18.0 2052 0.2924 0.9029
0.4037 19.0 2166 0.2486 0.9249
0.4037 20.0 2280 0.2049 0.9360
0.4037 21.0 2394 0.1854 0.9470
0.2072 22.0 2508 0.1803 0.9470
0.2072 23.0 2622 0.1634 0.9514
0.2072 24.0 2736 0.1615 0.9536
0.2072 25.0 2850 0.1560 0.9536
0.2072 26.0 2964 0.1512 0.9558
0.1222 27.0 3078 0.1470 0.9558
0.1222 28.0 3192 0.1519 0.9536
0.1222 29.0 3306 0.1505 0.9558
0.1222 30.0 3420 0.1510 0.9558

Framework versions

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