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---
license: llama2
library_name: peft
tags:
- generated_from_trainer
base_model: meta-llama/Llama-2-7b-hf
model-index:
- name: llama_domar_finetune_e1
  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. -->

# llama_domar_finetune_e1

This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5880

## 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
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5895        | 0.2   | 50   | 0.6149          |
| 0.5736        | 0.4   | 100  | 0.6047          |
| 0.566         | 0.6   | 150  | 0.6001          |
| 0.5885        | 0.79  | 200  | 0.5974          |
| 0.5662        | 0.99  | 250  | 0.5966          |
| 0.515         | 1.19  | 300  | 0.5953          |
| 0.5473        | 1.39  | 350  | 0.5945          |
| 0.5126        | 1.59  | 400  | 0.5926          |
| 0.5027        | 1.79  | 450  | 0.5920          |
| 0.555         | 1.99  | 500  | 0.5902          |
| 0.4932        | 2.19  | 550  | 0.5912          |
| 0.5849        | 2.38  | 600  | 0.5899          |
| 0.544         | 2.58  | 650  | 0.5897          |
| 0.5308        | 2.78  | 700  | 0.5887          |
| 0.4975        | 2.98  | 750  | 0.5886          |
| 0.5555        | 3.18  | 800  | 0.5881          |
| 0.4924        | 3.38  | 850  | 0.5885          |
| 0.5424        | 3.58  | 900  | 0.5886          |
| 0.5217        | 3.78  | 950  | 0.5881          |
| 0.5179        | 3.97  | 1000 | 0.5881          |
| 0.5296        | 4.17  | 1050 | 0.5881          |
| 0.489         | 4.37  | 1100 | 0.5880          |
| 0.5308        | 4.57  | 1150 | 0.5880          |
| 0.4585        | 4.77  | 1200 | 0.5881          |
| 0.595         | 4.97  | 1250 | 0.5880          |


### Framework versions

- PEFT 0.8.2
- Transformers 4.38.1
- Pytorch 2.2.0+cu118
- Datasets 2.17.1
- Tokenizers 0.15.2