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lemexp-task1-v2-lemma_object_full-deepseek-coder-1.3b-base-ddp-8lr-v2

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lemexp-task1-v2-lemma_object_full-deepseek-coder-1.3b-base-ddp-8lr-v2 / README.md
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metadata
library_name: peft
license: other
base_model: deepseek-ai/deepseek-coder-1.3b-base
tags:
  - generated_from_trainer
model-index:
  - name: lemexp-task1-v2-lemma_object_full-deepseek-coder-1.3b-base-ddp-8lr-v2
    results: []

lemexp-task1-v2-lemma_object_full-deepseek-coder-1.3b-base-ddp-8lr-v2

This model is a fine-tuned version of deepseek-ai/deepseek-coder-1.3b-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2261

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: 0.0008
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 16
  • total_eval_batch_size: 16
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 12
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
0.4519 0.2 3094 0.4528
0.4192 0.4 6188 0.4162
0.4051 0.6 9282 0.4043
0.3928 0.8 12376 0.3904
0.3846 1.0 15470 0.3827
0.3797 1.2 18564 0.3772
0.3744 1.4 21658 0.3697
0.3697 1.6 24752 0.3640
0.3643 1.8 27846 0.3624
0.3614 2.0 30940 0.3526
0.3546 2.2 34034 0.3512
0.3503 2.4 37128 0.3487
0.345 2.6 40222 0.3421
0.3449 2.8 43316 0.3431
0.3421 3.0 46410 0.3432
0.335 3.2 49504 0.3359
0.3351 3.4 52598 0.3336
0.33 3.6 55692 0.3340
0.3283 3.8 58786 0.3282
0.3266 4.0 61880 0.3166
0.317 4.2 64974 0.3149
0.3122 4.4 68068 0.3149
0.313 4.6 71162 0.3147
0.3043 4.8 74256 0.3130
0.3019 5.0 77350 0.3036
0.2952 5.2 80444 0.3000
0.2996 5.4 83538 0.3003
0.2957 5.6 86632 0.2993
0.2935 5.8 89726 0.3047
0.2885 6.0 92820 0.2928
0.2755 6.2 95914 0.2915
0.2763 6.4 99008 0.2875
0.2755 6.6 102102 0.2855
0.2811 6.8 105196 0.2812
0.2704 7.0 108290 0.2796
0.26 7.2 111384 0.2776
0.2564 7.4 114478 0.2691
0.2613 7.6 117572 0.2702
0.2568 7.8 120666 0.2684
0.2579 8.0 123760 0.2643
0.2422 8.2 126854 0.2624
0.243 8.4 129948 0.2619
0.2421 8.6 133042 0.2583
0.2455 8.8 136136 0.2575
0.2428 9.0 139230 0.2511
0.2286 9.2 142324 0.2478
0.227 9.4 145418 0.2507
0.2246 9.6 148512 0.2474
0.2273 9.8 151606 0.2452
0.2211 10.0 154700 0.2432
0.2117 10.2 157794 0.2434
0.2098 10.4 160888 0.2377
0.2092 10.6 163982 0.2376
0.2073 10.8 167076 0.2355
0.2051 11.0 170170 0.2303
0.1966 11.2 173264 0.2321
0.1923 11.4 176358 0.2294
0.1913 11.6 179452 0.2275
0.189 11.8 182546 0.2267
0.1924 12.0 185640 0.2261

Framework versions

  • PEFT 0.14.0
  • Transformers 4.47.0
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0