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---
library_name: transformers
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: large_crafting_sft_fail
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. -->
# large_crafting_sft_fail
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the identity and the large_crafting_sft_fail datasets.
It achieves the following results on the evaluation set:
- Loss: 0.3223
## 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: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 16
- 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: 1.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.5429 | 0.0323 | 50 | 0.4980 |
| 0.5398 | 0.0646 | 100 | 0.4740 |
| 0.5484 | 0.0969 | 150 | 0.4833 |
| 0.5265 | 0.1291 | 200 | 0.4780 |
| 0.5278 | 0.1614 | 250 | 0.4793 |
| 0.5259 | 0.1937 | 300 | 0.4519 |
| 0.5293 | 0.2260 | 350 | 0.4497 |
| 0.5098 | 0.2583 | 400 | 0.4303 |
| 0.482 | 0.2906 | 450 | 0.4249 |
| 0.4683 | 0.3229 | 500 | 0.4224 |
| 0.4572 | 0.3552 | 550 | 0.4136 |
| 0.456 | 0.3874 | 600 | 0.4034 |
| 0.4606 | 0.4197 | 650 | 0.3983 |
| 0.4285 | 0.4520 | 700 | 0.3874 |
| 0.4499 | 0.4843 | 750 | 0.3806 |
| 0.4198 | 0.5166 | 800 | 0.3685 |
| 0.4208 | 0.5489 | 850 | 0.3661 |
| 0.4379 | 0.5812 | 900 | 0.3637 |
| 0.4075 | 0.6134 | 950 | 0.3558 |
| 0.4121 | 0.6457 | 1000 | 0.3513 |
| 0.4112 | 0.6780 | 1050 | 0.3454 |
| 0.4041 | 0.7103 | 1100 | 0.3457 |
| 0.3852 | 0.7426 | 1150 | 0.3384 |
| 0.3656 | 0.7749 | 1200 | 0.3340 |
| 0.384 | 0.8072 | 1250 | 0.3303 |
| 0.3605 | 0.8395 | 1300 | 0.3276 |
| 0.3593 | 0.8717 | 1350 | 0.3247 |
| 0.3624 | 0.9040 | 1400 | 0.3233 |
| 0.3734 | 0.9363 | 1450 | 0.3229 |
| 0.3609 | 0.9686 | 1500 | 0.3223 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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