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metadata
tags:
  - generated_from_trainer
datasets:
  - pile-instruct/
metrics:
  - accuracy
model-index:
  - name: layer_4,5,6,7,8
    results:
      - task:
          type: text-generation
          name: Causal Language Modeling
        dataset:
          name: pile-instruct/
          type: pile-instruct/
          split: None
        metrics:
          - type: accuracy
            value: 0.3842425129408517
            name: Accuracy

layer_4,5,6,7,8

This model is a fine-tuned version of P1ayer-1/pythia-deduped-1b-chat-base on the pile-instruct/ dataset. It achieves the following results on the evaluation set:

  • Loss: 4.9648
  • Accuracy: 0.3842

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: 0.0001
  • train_batch_size: 12
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 96
  • total_eval_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • training_steps: 6000

Training results

Training Loss Epoch Step Accuracy Validation Loss
7.4574 0.1 200 0.1688 7.4961
7.0445 0.2 400 0.1997 7.0547
6.7483 0.3 600 0.2190 6.7930
6.4568 0.4 800 0.2376 6.5703
6.2865 0.5 1000 0.2552 6.375
6.1028 0.6 1200 0.2793 6.1484
5.8888 0.7 1400 0.2982 5.9570
5.7362 0.8 1600 0.3121 5.8008
5.6507 0.9 1800 0.3238 5.6797
5.565 1.0 2000 0.3318 5.5781
5.4688 1.1 2200 0.3392 5.4961
5.4044 1.2 2400 0.3456 5.4219
5.3323 1.3 2600 0.3516 5.3594
5.2598 1.4 2800 0.3562 5.3047
5.2159 1.5 3000 0.3596 5.2578
5.1992 1.6 3200 0.3638 5.2148
5.1429 1.69 3400 0.3672 5.1797
5.095 1.79 3600 0.3696 5.1445
5.0646 1.89 3800 0.3715 5.1172
5.059 1.99 4000 0.3742 5.0859
5.0152 2.09 4200 0.3756 5.0664
5.0251 2.19 4400 0.3769 5.0469
5.022 2.29 4600 0.3790 5.0273
4.9939 2.39 4800 0.3798 5.0156
4.924 2.49 5000 0.3811 5.0
4.9335 2.59 5200 0.3821 4.9883
4.9231 2.69 5400 0.3829 4.9805
4.8886 2.79 5600 4.9727 0.3835
4.9419 2.89 5800 4.9648 0.3843
4.9227 2.99 6000 4.9648 0.3842

Framework versions

  • Transformers 4.28.1
  • Pytorch 2.0.0+cu117
  • Datasets 2.11.0
  • Tokenizers 0.13.3

Wandb Report

https://wandb.ai/ontocord/pythia-1b-deduped-layer-test-min-pile-instruct/runs/kqlipkt3