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update model card README.md
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metadata
license: other
tags:
  - generated_from_trainer
datasets:
  - AlekseyKorshuk/amazon-reviews-input-output
metrics:
  - accuracy
model-index:
  - name: amazon-reviews-input-output-6.7b
    results:
      - task:
          name: Causal Language Modeling
          type: text-generation
        dataset:
          name: AlekseyKorshuk/amazon-reviews-input-output
          type: AlekseyKorshuk/amazon-reviews-input-output
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.03882113821138211

amazon-reviews-input-output-6.7b

This model is a fine-tuned version of facebook/opt-6.7b on the AlekseyKorshuk/amazon-reviews-input-output dataset. It achieves the following results on the evaluation set:

  • Loss: 2.8574
  • Accuracy: 0.0388
  • Samples: 100
  • Perplexity: 17.4166
  • Table: <wandb.data_types.Table object at 0x7fd30eb4e940>

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: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 64
  • total_eval_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.9912 0.06 1 2.7441 0.0404
2.9329 0.12 2 2.7441 0.0404
2.9138 0.19 3 2.8262 0.0389
2.9395 0.25 4 2.8262 0.0389
2.9109 0.31 5 2.7949 0.0399
2.8394 0.38 6 2.7461 0.0403
2.9365 0.44 7 2.7207 0.0399
2.7588 0.5 8 2.7070 0.0403
2.9751 0.56 9 2.6816 0.0407
2.844 0.62 10 2.6738 0.0404
2.731 0.69 11 2.6680 0.0406
2.7434 0.75 12 2.6699 0.0404
2.9043 0.81 13 2.6855 0.0400
2.8564 0.88 14 2.6855 0.0400
2.8716 0.94 15 2.6855 0.0400
2.896 1.0 16 2.6953 0.0398
1.9858 1.06 17 2.7070 0.0400
2.0563 1.12 18 2.7285 0.0400
2.04 1.19 19 2.7676 0.0398
1.9885 1.25 20 2.7910 0.0396
2.09 1.31 21 2.7969 0.0393
2.059 1.38 22 2.8105 0.0395
2.0498 1.44 23 2.7930 0.0398
1.9568 1.5 24 2.7910 0.0401
2.1418 1.56 25 2.7930 0.0398
1.975 1.62 26 2.7930 0.0397
1.996 1.69 27 2.7949 0.0393
1.9617 1.75 28 2.8047 0.0392
2.2062 1.81 29 2.8145 0.0388
1.9929 1.88 30 2.8145 0.0386
1.9235 1.94 31 2.8281 0.0390
1.9127 2.0 32 2.8574 0.0388

Framework versions

  • Transformers 4.25.0.dev0
  • Pytorch 1.12.1+cu113
  • Datasets 2.3.2
  • Tokenizers 0.12.1