TinyStoriesV2_Llama-3.2-1B-h1d849vi
This model is a fine-tuned version of meta-llama/Llama-3.2-1B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.3234
- Model Preparation Time: 0.0015
- Token Accuracy: 0.5025
- Token Error Rate: 0.4975
- Perplexity: inf
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- 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: constant_with_warmup
- lr_scheduler_warmup_ratio: 0.001
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Token Accuracy | Token Error Rate | Perplexity |
|---|---|---|---|---|---|---|---|
| No log | 0 | 0 | 12.1341 | 0.0015 | 0.0000 | 1.0000 | inf |
| 3.8312 | 0.16 | 100 | 4.1267 | 0.0015 | 0.2896 | 0.7104 | inf |
| 3.4808 | 0.32 | 200 | 3.5028 | 0.0015 | 0.3494 | 0.6506 | inf |
| 3.0317 | 0.48 | 300 | 3.1823 | 0.0015 | 0.3890 | 0.6110 | inf |
| 2.9984 | 0.64 | 400 | 2.9667 | 0.0015 | 0.4173 | 0.5827 | inf |
| 2.8955 | 0.8 | 500 | 2.8102 | 0.0015 | 0.4363 | 0.5637 | inf |
| 2.6872 | 0.96 | 600 | 2.6984 | 0.0015 | 0.4490 | 0.5510 | inf |
| 2.2615 | 1.12 | 700 | 2.6066 | 0.0015 | 0.4630 | 0.5370 | inf |
| 2.3631 | 1.28 | 800 | 2.5503 | 0.0015 | 0.4701 | 0.5299 | inf |
| 2.289 | 1.44 | 900 | 2.4962 | 0.0015 | 0.4782 | 0.5218 | inf |
| 2.4212 | 1.6 | 1000 | 2.4481 | 0.0015 | 0.4839 | 0.5161 | inf |
| 2.1475 | 1.76 | 1100 | 2.3975 | 0.0015 | 0.4903 | 0.5097 | inf |
| 2.3243 | 1.92 | 1200 | 2.3584 | 0.0015 | 0.4942 | 0.5058 | inf |
| 1.5243 | 2.08 | 1300 | 2.3580 | 0.0015 | 0.5012 | 0.4988 | inf |
| 1.5952 | 2.24 | 1400 | 2.3582 | 0.0015 | 0.4996 | 0.5004 | inf |
| 1.5865 | 2.4 | 1500 | 2.3528 | 0.0015 | 0.5001 | 0.4999 | inf |
| 1.653 | 2.56 | 1600 | 2.3418 | 0.0015 | 0.5018 | 0.4982 | inf |
| 1.3684 | 2.7200 | 1700 | 2.3310 | 0.0015 | 0.5023 | 0.4977 | inf |
| 1.6193 | 2.88 | 1800 | 2.3234 | 0.0015 | 0.5025 | 0.4975 | inf |
| 0.9412 | 3.04 | 1900 | 2.3864 | 0.0015 | 0.5034 | 0.4966 | inf |
| 0.9458 | 3.2 | 2000 | 2.4532 | 0.0015 | 0.4999 | 0.5001 | inf |
| 0.7451 | 3.36 | 2100 | 2.4952 | 0.0015 | 0.4971 | 0.5029 | inf |
| 0.8707 | 3.52 | 2200 | 2.5129 | 0.0015 | 0.4955 | 0.5045 | inf |
| 0.777 | 3.68 | 2300 | 2.5154 | 0.0015 | 0.4959 | 0.5041 | inf |
| 0.8348 | 3.84 | 2400 | 2.5380 | 0.0015 | 0.4940 | 0.5060 | inf |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1