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---
library_name: transformers
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: IE_L3_1000steps_1e6rate_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. -->
# IE_L3_1000steps_1e6rate_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: 1.6162
## 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-06
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8795 | 0.4 | 50 | 1.7359 |
| 1.5557 | 0.8 | 100 | 1.5149 |
| 1.5505 | 1.2 | 150 | 1.4878 |
| 1.4839 | 1.6 | 200 | 1.4811 |
| 1.4928 | 2.0 | 250 | 1.4778 |
| 1.3677 | 2.4 | 300 | 1.4931 |
| 1.3947 | 2.8 | 350 | 1.4940 |
| 1.1632 | 3.2 | 400 | 1.5277 |
| 1.2544 | 3.6 | 450 | 1.5207 |
| 1.147 | 4.0 | 500 | 1.5292 |
| 1.1403 | 4.4 | 550 | 1.5664 |
| 1.0704 | 4.8 | 600 | 1.5711 |
| 1.0585 | 5.2 | 650 | 1.6079 |
| 1.0515 | 5.6 | 700 | 1.6006 |
| 0.9566 | 6.0 | 750 | 1.6039 |
| 0.9733 | 6.4 | 800 | 1.6169 |
| 0.9837 | 6.8 | 850 | 1.6162 |
| 0.9766 | 7.2 | 900 | 1.6158 |
| 0.924 | 7.6 | 950 | 1.6164 |
| 1.0258 | 8.0 | 1000 | 1.6162 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.0.0+cu117
- Datasets 3.0.0
- Tokenizers 0.19.1
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