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metadata
license: other
library_name: peft
tags:
  - trl
  - sft
  - generated_from_trainer
base_model: google/gemma-2b
model-index:
  - name: gemma-2b-spanishbillionwords
    results: []

gemma-2b-spanishbillionwords

This model is a fine-tuned version of google/gemma-2b on Spanish Billion Words. This is the base Gemma model fine-tuned to perform better on spanish language. It achieves the following results on the evaluation set:

  • Loss: 4.3306

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: 0.0003
  • train_batch_size: 1
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 2
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1
  • training_steps: 60
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
5.1254 0.0 1 5.0205
4.3187 0.0 2 5.0029
3.8173 0.0 3 4.9801
5.3879 0.0 4 4.9582
5.718 0.0 5 4.9343
5.8628 0.0 6 4.9104
4.5401 0.0 7 4.8830
4.4219 0.0 8 4.8539
5.5169 0.0 9 4.8234
4.813 0.0 10 4.7878
4.2111 0.0 11 4.7576
4.6504 0.0 12 4.7314
3.7923 0.0 13 4.7116
3.7773 0.0 14 4.6890
4.6773 0.0 15 4.6616
3.0179 0.0 16 4.6329
3.8922 0.0 17 4.6099
4.3289 0.0 18 4.5940
5.0925 0.0 19 4.5822
4.6499 0.0 20 4.5711
3.9758 0.0 21 4.5585
4.593 0.0 22 4.5454
5.2496 0.0 23 4.5346
4.2548 0.0 24 4.5217
3.5209 0.0 25 4.5059
4.4781 0.0 26 4.4930
5.4472 0.0 27 4.4834
4.1987 0.0 28 4.4756
5.2324 0.0 29 4.4684
4.8068 0.0 30 4.4593
3.5455 0.0 31 4.4521
3.6516 0.0 32 4.4415
4.1368 0.0 33 4.4289
6.4659 0.0 34 4.4289
3.434 0.0 35 4.4173
3.9518 0.0 36 4.4085
3.0758 0.0 37 4.4008
3.6492 0.0 38 4.3930
4.0352 0.0 39 4.3857
5.6527 0.0 40 4.3799
4.233 0.0 41 4.3747
5.4082 0.0 42 4.3702
5.1255 0.0 43 4.3661
4.4567 0.0 44 4.3622
4.1874 0.0 45 4.3587
4.3441 0.0 46 4.3555
4.1636 0.0 47 4.3524
4.3146 0.0 48 4.3495
4.6414 0.0 49 4.3473
4.3666 0.0 50 4.3451
3.8627 0.0 51 4.3427
4.5875 0.0 52 4.3406
6.0364 0.0 53 4.3387
4.5669 0.0 54 4.3369
4.5585 0.0 55 4.3353
2.7858 0.0 56 4.3340
4.1845 0.0 57 4.3329
4.4489 0.0 58 4.3319
5.3263 0.0 59 4.3311
5.3856 0.0 60 4.3306

Framework versions

  • PEFT 0.8.2
  • Transformers 4.38.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.17.0
  • Tokenizers 0.15.2