Baby-Llama-58M
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 6.1610
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: 0.00025
- train_batch_size: 128
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- num_epochs: 80
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 81.7512 | 1.0 | 2 | 74.4291 |
| 81.3083 | 2.0 | 4 | 73.3596 |
| 78.6216 | 3.0 | 6 | 71.5365 |
| 80.396 | 4.0 | 8 | 70.3538 |
| 75.3713 | 5.0 | 10 | 67.4044 |
| 74.0418 | 6.0 | 12 | 64.0233 |
| 70.1637 | 7.0 | 14 | 60.8437 |
| 67.5864 | 8.0 | 16 | 57.9300 |
| 64.8984 | 9.0 | 18 | 55.0383 |
| 61.2535 | 10.0 | 20 | 52.0253 |
| 57.6171 | 11.0 | 22 | 48.9365 |
| 54.2922 | 12.0 | 24 | 45.8747 |
| 50.3849 | 13.0 | 26 | 43.0132 |
| 49.0703 | 14.0 | 28 | 40.4715 |
| 45.5158 | 15.0 | 30 | 38.1415 |
| 44.3002 | 16.0 | 32 | 35.9572 |
| 41.2208 | 17.0 | 34 | 33.8684 |
| 39.8837 | 18.0 | 36 | 31.8991 |
| 38.1152 | 19.0 | 38 | 29.8574 |
| 35.239 | 20.0 | 40 | 28.0249 |
| 33.6748 | 21.0 | 42 | 26.4792 |
| 30.4729 | 22.0 | 44 | 25.4216 |
| 29.436 | 23.0 | 46 | 24.1119 |
| 27.72 | 24.0 | 48 | 22.8196 |
| 25.5231 | 25.0 | 50 | 21.7862 |
| 24.8119 | 26.0 | 52 | 20.4891 |
| 23.3658 | 27.0 | 54 | 19.3795 |
| 21.4143 | 28.0 | 56 | 18.1634 |
| 20.032 | 29.0 | 58 | 17.0348 |
| 18.43 | 30.0 | 60 | 16.1163 |
| 16.897 | 31.0 | 62 | 15.2508 |
| 15.7483 | 32.0 | 64 | 14.3147 |
| 15.1794 | 33.0 | 66 | 13.5753 |
| 13.7129 | 34.0 | 68 | 12.8868 |
| 12.6031 | 35.0 | 70 | 12.6810 |
| 11.8192 | 36.0 | 72 | 11.9060 |
| 11.6487 | 37.0 | 74 | 11.3454 |
| 10.9525 | 38.0 | 76 | 10.8465 |
| 10.2164 | 39.0 | 78 | 10.1026 |
| 9.5492 | 40.0 | 80 | 9.6511 |
| 9.0438 | 41.0 | 82 | 9.2800 |
| 8.6141 | 42.0 | 84 | 8.8036 |
| 7.9373 | 43.0 | 86 | 8.6612 |
| 7.5371 | 44.0 | 88 | 8.1757 |
| 7.3186 | 45.0 | 90 | 8.1665 |
| 7.033 | 46.0 | 92 | 7.7424 |
| 6.7923 | 47.0 | 94 | 7.6650 |
| 6.4384 | 48.0 | 96 | 7.4306 |
| 6.2449 | 49.0 | 98 | 7.4175 |
| 6.1012 | 50.0 | 100 | 7.1466 |
| 6.0502 | 51.0 | 102 | 7.1740 |
| 5.7839 | 52.0 | 104 | 6.9619 |
| 5.6905 | 53.0 | 106 | 6.9416 |
| 5.665 | 54.0 | 108 | 6.7945 |
| 5.5401 | 55.0 | 110 | 6.7485 |
| 5.4773 | 56.0 | 112 | 6.6674 |
| 5.4169 | 57.0 | 114 | 6.6132 |
| 5.3628 | 58.0 | 116 | 6.5787 |
| 5.2021 | 59.0 | 118 | 6.4972 |
| 5.2817 | 60.0 | 120 | 6.4866 |
| 5.1901 | 61.0 | 122 | 6.4256 |
| 5.1268 | 62.0 | 124 | 6.3659 |
| 5.1105 | 63.0 | 126 | 6.3563 |
| 5.0539 | 64.0 | 128 | 6.3159 |
| 4.9715 | 65.0 | 130 | 6.3178 |
| 4.872 | 66.0 | 132 | 6.2741 |
| 4.9422 | 67.0 | 134 | 6.2699 |
| 4.944 | 68.0 | 136 | 6.2551 |
| 4.9487 | 69.0 | 138 | 6.2148 |
| 4.8968 | 70.0 | 140 | 6.2089 |
| 4.822 | 71.0 | 142 | 6.2093 |
| 4.965 | 72.0 | 144 | 6.1853 |
| 4.8401 | 73.0 | 146 | 6.1747 |
| 4.8539 | 74.0 | 148 | 6.1738 |
| 4.7751 | 75.0 | 150 | 6.1674 |
| 4.8871 | 76.0 | 152 | 6.1644 |
| 4.9347 | 77.0 | 154 | 6.1618 |
| 4.8009 | 78.0 | 156 | 6.1613 |
| 4.8121 | 79.0 | 158 | 6.1610 |
| 4.8048 | 80.0 | 160 | 6.1610 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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