---
license: other
base_model: yahma/llama-7b-hf
tags:
- generated_from_trainer
model-index:
- name: V0224P8
  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. -->

# V0224P8

This model is a fine-tuned version of [yahma/llama-7b-hf](https://huggingface.co/yahma/llama-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7483

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 20
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0988        | 0.13  | 10   | 1.0588          |
| 0.9892        | 0.26  | 20   | 0.9511          |
| 0.9008        | 0.39  | 30   | 0.8673          |
| 0.8366        | 0.52  | 40   | 0.8299          |
| 0.8139        | 0.65  | 50   | 0.8099          |
| 0.7954        | 0.78  | 60   | 0.7970          |
| 0.7704        | 0.91  | 70   | 0.7862          |
| 0.7614        | 1.04  | 80   | 0.7788          |
| 0.7322        | 1.17  | 90   | 0.7733          |
| 0.7482        | 1.3   | 100  | 0.7694          |
| 0.7366        | 1.43  | 110  | 0.7645          |
| 0.7261        | 1.55  | 120  | 0.7605          |
| 0.7171        | 1.68  | 130  | 0.7578          |
| 0.7274        | 1.81  | 140  | 0.7552          |
| 0.7313        | 1.94  | 150  | 0.7514          |
| 0.7069        | 2.07  | 160  | 0.7516          |
| 0.6858        | 2.2   | 170  | 0.7503          |
| 0.6988        | 2.33  | 180  | 0.7498          |
| 0.6903        | 2.46  | 190  | 0.7490          |
| 0.6926        | 2.59  | 200  | 0.7490          |
| 0.6952        | 2.72  | 210  | 0.7485          |
| 0.6925        | 2.85  | 220  | 0.7484          |
| 0.6938        | 2.98  | 230  | 0.7483          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1