linker_v6 / README.md
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metadata
base_model: jarod0411/zinc10M_gpt2_SMILES_bpe_combined_step1
tags:
  - generated_from_trainer
datasets:
  - jarod0411/linker_v6
metrics:
  - accuracy
model-index:
  - name: linker_v6
    results:
      - task:
          name: Causal Language Modeling
          type: text-generation
        dataset:
          name: jarod0411/linker_v6
          type: jarod0411/linker_v6
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8994679101285066

linker_v6

This model is a fine-tuned version of jarod0411/zinc10M_gpt2_SMILES_bpe_combined_step1 on the jarod0411/linker_v6 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3103
  • Accuracy: 0.8995

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: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 1
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 128
  • total_eval_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.3747 1.0 43879 0.3539 0.8870
0.3495 2.0 87758 0.3322 0.8936
0.3387 3.0 131637 0.3240 0.8959
0.3322 4.0 175516 0.3194 0.8971
0.3279 5.0 219395 0.3164 0.8978
0.325 6.0 263274 0.3140 0.8985
0.3231 7.0 307153 0.3125 0.8989
0.3213 8.0 351032 0.3114 0.8992
0.3201 9.0 394911 0.3107 0.8994
0.3191 10.0 438790 0.3103 0.8995

Framework versions

  • Transformers 4.38.0.dev0
  • Pytorch 2.2.0+cu121
  • Datasets 2.17.0
  • Tokenizers 0.15.2