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---
license: apache-2.0
base_model: Isotonic/smol_llama-4x220M-MoE
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: smol_llama_x
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. -->
# smol_llama_x
This model is a fine-tuned version of [Isotonic/smol_llama-4x220M-MoE](https://huggingface.co/Isotonic/smol_llama-4x220M-MoE) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5906
- Accuracy: 0.6799
## 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-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 211 | 1.4545 | 0.6908 |
| No log | 2.0 | 422 | 1.4871 | 0.6881 |
| 1.4748 | 3.0 | 633 | 1.5353 | 0.6841 |
| 1.4748 | 4.0 | 844 | 1.5906 | 0.6799 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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