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Llama-31-8B_task-1_180-samples_config-4

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Llama-31-8B_task-1_180-samples_config-4 / README.md
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metadata
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
  - GaetanMichelet/chat-60_ft_task-1
  - GaetanMichelet/chat-120_ft_task-1
  - GaetanMichelet/chat-180_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_180-samples_config-4
    results: []

Llama-31-8B_task-1_180-samples_config-4

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the GaetanMichelet/chat-60_ft_task-1, the GaetanMichelet/chat-120_ft_task-1 and the GaetanMichelet/chat-180_ft_task-1 datasets. It achieves the following results on the evaluation set:

  • Loss: 1.2589

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: 16
  • total_train_batch_size: 16
  • 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
2.0972 0.9412 8 2.0718
2.0234 2.0 17 2.0545
2.0324 2.9412 25 2.0288
2.0064 4.0 34 1.9798
1.9611 4.9412 42 1.9139
1.8283 6.0 51 1.8090
1.6817 6.9412 59 1.7011
1.5762 8.0 68 1.6085
1.5529 8.9412 76 1.5659
1.4817 10.0 85 1.5206
1.5125 10.9412 93 1.4816
1.3226 12.0 102 1.4352
1.3823 12.9412 110 1.3951
1.2564 14.0 119 1.3580
1.1936 14.9412 127 1.3305
1.2322 16.0 136 1.3061
1.1389 16.9412 144 1.2910
1.2119 18.0 153 1.2775
1.0796 18.9412 161 1.2672
1.088 20.0 170 1.2627
1.0344 20.9412 178 1.2631
1.0175 22.0 187 1.2589
0.9509 22.9412 195 1.2707
0.8574 24.0 204 1.2784
0.8673 24.9412 212 1.2985
0.8657 26.0 221 1.3300
0.7453 26.9412 229 1.3725
0.7771 28.0 238 1.3823
0.6941 28.9412 246 1.4508

Framework versions

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