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Llama-31-8B_task-1_60-samples_config-3_full

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metadata
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
  - GaetanMichelet/chat-60_ft_task-1
library_name: peft
license: llama3.1
tags:
  - alignment-handbook
  - trl
  - sft
  - generated_from_trainer
model-index:
  - name: Llama-31-8B_task-1_60-samples_config-3_full
    results: []

Llama-31-8B_task-1_60-samples_config-3_full

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the GaetanMichelet/chat-60_ft_task-1 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9224

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-05
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 150

Training results

Training Loss Epoch Step Validation Loss
2.5395 0.8696 5 2.4149
2.4512 1.9130 11 2.3973
2.4419 2.9565 17 2.3721
2.3921 4.0 23 2.3361
2.3357 4.8696 28 2.2954
2.3559 5.9130 34 2.2287
2.2622 6.9565 40 2.1654
2.186 8.0 46 2.0752
2.0842 8.8696 51 2.0000
2.0522 9.9130 57 1.8960
1.911 10.9565 63 1.7942
1.8076 12.0 69 1.6760
1.659 12.8696 74 1.5645
1.5002 13.9130 80 1.4214
1.309 14.9565 86 1.2940
1.2079 16.0 92 1.1837
1.1738 16.8696 97 1.1230
1.0304 17.9130 103 1.0781
1.0485 18.9565 109 1.0459
0.9687 20.0 115 1.0258
0.9883 20.8696 120 1.0147
0.974 21.9130 126 1.0013
0.9397 22.9565 132 0.9905
0.9522 24.0 138 0.9816
0.9115 24.8696 143 0.9739
0.9412 25.9130 149 0.9668
0.9168 26.9565 155 0.9610
0.9461 28.0 161 0.9547
0.8579 28.8696 166 0.9499
0.8857 29.9130 172 0.9454
0.8465 30.9565 178 0.9405
0.8681 32.0 184 0.9393
0.8257 32.8696 189 0.9344
0.8425 33.9130 195 0.9336
0.8405 34.9565 201 0.9281
0.8101 36.0 207 0.9283
0.7808 36.8696 212 0.9259
0.7971 37.9130 218 0.9259
0.7766 38.9565 224 0.9235
0.7748 40.0 230 0.9245
0.7476 40.8696 235 0.9253
0.7007 41.9130 241 0.9224
0.741 42.9565 247 0.9261
0.7371 44.0 253 0.9239
0.7239 44.8696 258 0.9323
0.671 45.9130 264 0.9269
0.7312 46.9565 270 0.9333
0.6826 48.0 276 0.9345
0.6472 48.8696 281 0.9393

Framework versions

  • PEFT 0.12.0
  • Transformers 4.44.0
  • Pytorch 2.1.2+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1