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---
library_name: transformers
license: llama3.2
base_model: meta-llama/Llama-3.2-1B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: mini_llama_crafting_sft_success_new_mem
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. -->
# mini_llama_crafting_sft_success_new_mem
This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) on the identity and the crafting_sft_success_new_mem datasets.
It achieves the following results on the evaluation set:
- Loss: 0.4032
## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8427 | 0.3380 | 50 | 1.1575 |
| 0.5411 | 0.6760 | 100 | 0.5065 |
| 0.519 | 1.0203 | 150 | 0.4361 |
| 0.3662 | 1.3583 | 200 | 0.4007 |
| 0.3679 | 1.6962 | 250 | 0.3948 |
| 0.3176 | 2.0406 | 300 | 0.3846 |
| 0.2141 | 2.3785 | 350 | 0.4076 |
| 0.2089 | 2.7165 | 400 | 0.3996 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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