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llama-lima

This model is a fine-tuned version of huggyllama/llama-7b on the GAIR/lima dataset. It achieves the following results on the evaluation set:

  • Loss: 1.9975

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: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 16
  • 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: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10.0

Training results

Training Loss Epoch Step Validation Loss
1.8892 1.0 6 1.7981
1.7346 2.0 12 1.7421
1.5782 3.0 18 1.6837
1.3988 4.0 24 1.7017
1.0825 5.0 30 1.7303
0.9252 6.0 36 1.8102
0.794 7.0 42 1.9195
0.7094 8.0 48 1.9669
0.6205 9.0 54 1.9970
0.5749 10.0 60 1.9975

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.2
  • Datasets 2.14.6
  • Tokenizers 0.15.2
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Dataset used to train pkarypis/llama-lima