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metadata
base_model: >-
  RefalMachine/llama3_extended_darulm_20_05_24_part1-2_64000_bpe_mean_init_03_07_24
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: llama3_extended_darulm_20_05_24_part1-2_64000_bpe_part1_lr2e4_bs256
    results: []

llama3_extended_darulm_20_05_24_part1-2_64000_bpe_part1_lr2e4_bs256

This model is a fine-tuned version of RefalMachine/llama3_extended_darulm_20_05_24_part1-2_64000_bpe_mean_init_03_07_24 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.1597
  • Accuracy: 0.5489

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: 0.0002
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 32
  • total_train_batch_size: 128
  • total_eval_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 1.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.4497 0.09 2000 2.2890 0.5302
2.4021 0.18 4000 2.2496 0.5356
2.3883 0.28 6000 2.2251 0.5390
2.3684 0.37 8000 2.2056 0.5416
2.3547 0.46 10000 2.1889 0.5438
2.3271 0.55 12000 2.1759 0.5459
2.3153 0.64 14000 2.1664 0.5476
2.3175 0.73 16000 2.1618 0.5485
2.3013 0.83 18000 2.1599 0.5488
2.3075 0.92 20000 2.1597 0.5489

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.3.0a0+6ddf5cf85e.nv24.04
  • Datasets 2.18.0
  • Tokenizers 0.15.2