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gemma-2b-spanishbillionwords
mcamara/gemma-2b-spanishbillionwords
gemma-2b-spanishbillionwords is a machine learning model from mcamara. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as other.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- other
- Access
- Public
- Created
- Mar 11, 2024
- Updated
- Mar 12, 2024
- SHA
- 8d2345af
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
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
- Library
- peft
- License
- other
- Created
- Mar 11, 2024
- Updated
- Mar 12, 2024