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indic-bert-finetuned-ours-DS

Text Classification
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PyTorch
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albert
Generated from Trainer
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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: indic-bert-finetuned-ours-DS
    results: []

indic-bert-finetuned-ours-DS

This model is a fine-tuned version of ai4bharat/indic-bert on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0941
  • Accuracy: 0.275
  • Precision: 0.3056
  • Recall: 0.3467
  • F1: 0.1803

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: 1e-07
  • train_batch_size: 16
  • eval_batch_size: 32
  • seed: 43
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 25

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
1.0988 0.99 99 1.0984 0.3 0.3611 0.3661 0.2750
1.0981 1.98 198 1.0980 0.29 0.2713 0.3568 0.1997
1.0981 2.97 297 1.0977 0.315 0.3029 0.3736 0.2259
1.0976 3.96 396 1.0974 0.3 0.2816 0.3601 0.2122
1.0976 4.95 495 1.0971 0.295 0.2780 0.3601 0.2041
1.097 5.94 594 1.0968 0.29 0.2680 0.3533 0.2012
1.0962 6.93 693 1.0965 0.3 0.2816 0.3601 0.2122
1.0963 7.92 792 1.0963 0.29 0.2761 0.3533 0.2012
1.0969 8.91 891 1.0961 0.3 0.2895 0.3601 0.2122
1.0958 9.9 990 1.0958 0.3 0.2895 0.3601 0.2122
1.0959 10.89 1089 1.0956 0.3 0.2983 0.3601 0.2122
1.0953 11.88 1188 1.0954 0.3 0.2983 0.3601 0.2122
1.0955 12.87 1287 1.0952 0.295 0.3019 0.3567 0.2067
1.0948 13.86 1386 1.0951 0.295 0.3083 0.3601 0.2040
1.095 14.85 1485 1.0949 0.29 0.3013 0.3568 0.1983
1.0951 15.84 1584 1.0948 0.29 0.3013 0.3568 0.1983
1.0948 16.83 1683 1.0946 0.29 0.3143 0.3568 0.1982
1.0942 17.82 1782 1.0945 0.29 0.3291 0.3568 0.1982
1.0949 18.81 1881 1.0944 0.28 0.3145 0.3500 0.1863
1.095 19.8 1980 1.0943 0.275 0.3056 0.3467 0.1803
1.0945 20.79 2079 1.0943 0.275 0.3056 0.3467 0.1803
1.0942 21.78 2178 1.0942 0.275 0.3056 0.3467 0.1803
1.0938 22.77 2277 1.0942 0.275 0.3056 0.3467 0.1803
1.0953 23.76 2376 1.0941 0.275 0.3056 0.3467 0.1803
1.0943 24.75 2475 1.0941 0.275 0.3056 0.3467 0.1803

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.10.1+cu111
  • Datasets 2.3.2
  • Tokenizers 0.12.1