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---
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Transaminitis_L3_1000rate_1e8_SFT
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. -->
# Transaminitis_L3_1000rate_1e8_SFT
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6870
## 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-08
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.684 | 0.2 | 25 | 2.6901 |
| 2.6773 | 0.4 | 50 | 2.6883 |
| 2.6627 | 0.6 | 75 | 2.6887 |
| 2.6575 | 0.8 | 100 | 2.6912 |
| 2.6624 | 1.0 | 125 | 2.6897 |
| 2.6725 | 1.2 | 150 | 2.6884 |
| 2.6661 | 1.4 | 175 | 2.6891 |
| 2.692 | 1.6 | 200 | 2.6879 |
| 2.6801 | 1.8 | 225 | 2.6855 |
| 2.6683 | 2.0 | 250 | 2.6867 |
| 2.6812 | 2.2 | 275 | 2.6857 |
| 2.6786 | 2.4 | 300 | 2.6862 |
| 2.6726 | 2.6 | 325 | 2.6863 |
| 2.6733 | 2.8 | 350 | 2.6870 |
| 2.664 | 3.0 | 375 | 2.6880 |
| 2.665 | 3.2 | 400 | 2.6871 |
| 2.671 | 3.4 | 425 | 2.6854 |
| 2.6788 | 3.6 | 450 | 2.6870 |
| 2.673 | 3.8 | 475 | 2.6880 |
| 2.648 | 4.0 | 500 | 2.6863 |
| 2.6661 | 4.2 | 525 | 2.6866 |
| 2.6707 | 4.4 | 550 | 2.6856 |
| 2.6799 | 4.6 | 575 | 2.6870 |
| 2.673 | 4.8 | 600 | 2.6874 |
| 2.6757 | 5.0 | 625 | 2.6856 |
| 2.6658 | 5.2 | 650 | 2.6874 |
| 2.6712 | 5.4 | 675 | 2.6869 |
| 2.674 | 5.6 | 700 | 2.6866 |
| 2.6804 | 5.8 | 725 | 2.6866 |
| 2.6755 | 6.0 | 750 | 2.6872 |
| 2.685 | 6.2 | 775 | 2.6870 |
| 2.6701 | 6.4 | 800 | 2.6870 |
| 2.6893 | 6.6 | 825 | 2.6870 |
| 2.6722 | 6.8 | 850 | 2.6870 |
| 2.6783 | 7.0 | 875 | 2.6870 |
| 2.6671 | 7.2 | 900 | 2.6870 |
| 2.6691 | 7.4 | 925 | 2.6870 |
| 2.6947 | 7.6 | 950 | 2.6870 |
| 2.6773 | 7.8 | 975 | 2.6870 |
| 2.6737 | 8.0 | 1000 | 2.6870 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.0.0+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1
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