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---
library_name: transformers
base_model: roneneldan/TinyStories-1M
tags:
- generated_from_trainer
model-index:
- name: tinylm1M-stella-2sent_32clust-2025-04-04-13-49
results: []
---
<!-- 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. -->
# tinylm1M-stella-2sent_32clust-2025-04-04-13-49
This model is a fine-tuned version of [roneneldan/TinyStories-1M](https://huggingface.co/roneneldan/TinyStories-1M) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2485
## 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: 5e-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 2.603 | 0.8418 | 500 | 2.5493 |
| 2.5641 | 1.6835 | 1000 | 2.5072 |
| 2.5856 | 2.5253 | 1500 | 2.4748 |
| 2.4812 | 3.3670 | 2000 | 2.4526 |
| 2.3806 | 4.2088 | 2500 | 2.4287 |
| 2.365 | 5.0505 | 3000 | 2.4067 |
| 2.3335 | 5.8923 | 3500 | 2.3860 |
| 2.3483 | 6.7340 | 4000 | 2.3676 |
| 2.3202 | 7.5758 | 4500 | 2.3528 |
| 2.3296 | 8.4175 | 5000 | 2.3395 |
| 2.2774 | 9.2593 | 5500 | 2.3251 |
| 2.2768 | 10.1010 | 6000 | 2.3136 |
| 2.312 | 10.9428 | 6500 | 2.3000 |
| 2.2991 | 11.7845 | 7000 | 2.2903 |
| 2.3076 | 12.6263 | 7500 | 2.2813 |
| 2.1882 | 13.4680 | 8000 | 2.2751 |
| 2.2872 | 14.3098 | 8500 | 2.2669 |
| 2.3859 | 15.1515 | 9000 | 2.2619 |
| 2.2089 | 15.9933 | 9500 | 2.2582 |
| 2.3199 | 16.8350 | 10000 | 2.2533 |
| 2.1989 | 17.6768 | 10500 | 2.2504 |
| 2.2267 | 18.5185 | 11000 | 2.2499 |
| 2.1404 | 19.3603 | 11500 | 2.2485 |
### Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
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