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---
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Summary_L3_1000steps_1e5rate_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. -->

# Summary_L3_1000steps_1e5rate_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: 0.7019

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7518        | 0.2   | 50   | 0.6955          |
| 0.7657        | 0.4   | 100  | 0.7030          |
| 0.7138        | 0.6   | 150  | 0.6648          |
| 0.6394        | 0.8   | 200  | 0.6382          |
| 0.5783        | 1.0   | 250  | 0.6033          |
| 0.4656        | 1.2   | 300  | 0.5986          |
| 0.4742        | 1.4   | 350  | 0.5881          |
| 0.417         | 1.6   | 400  | 0.5612          |
| 0.3351        | 1.8   | 450  | 0.5599          |
| 0.4481        | 2.0   | 500  | 0.5488          |
| 0.185         | 2.2   | 550  | 0.6115          |
| 0.1621        | 2.4   | 600  | 0.6201          |
| 0.1701        | 2.6   | 650  | 0.6293          |
| 0.1325        | 2.8   | 700  | 0.6154          |
| 0.166         | 3.0   | 750  | 0.6194          |
| 0.0347        | 3.2   | 800  | 0.6931          |
| 0.0422        | 3.4   | 850  | 0.7013          |
| 0.0449        | 3.6   | 900  | 0.7014          |
| 0.0358        | 3.8   | 950  | 0.7020          |
| 0.0422        | 4.0   | 1000 | 0.7019          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.0.0+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1