---
license: other
base_model: yahma/llama-7b-hf
tags:
- generated_from_trainer
model-index:
- name: V0305P8
  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. -->

# V0305P8

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: 0.0762

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.877         | 0.09  | 10   | 0.8565          |
| 0.3259        | 0.17  | 20   | 0.1568          |
| 0.1567        | 0.26  | 30   | 0.1546          |
| 0.152         | 0.34  | 40   | 0.1487          |
| 0.1493        | 0.43  | 50   | 0.1432          |
| 0.149         | 0.51  | 60   | 0.1259          |
| 0.1321        | 0.6   | 70   | 0.1074          |
| 0.1234        | 0.68  | 80   | 0.1031          |
| 0.1094        | 0.77  | 90   | 0.0987          |
| 0.11          | 0.85  | 100  | 0.0989          |
| 0.1084        | 0.94  | 110  | 0.0971          |
| 0.1055        | 1.02  | 120  | 0.0967          |
| 0.0937        | 1.11  | 130  | 0.0920          |
| 0.0917        | 1.19  | 140  | 0.0874          |
| 0.0893        | 1.28  | 150  | 0.0819          |
| 0.09          | 1.37  | 160  | 0.0808          |
| 0.0882        | 1.45  | 170  | 0.0827          |
| 0.0832        | 1.54  | 180  | 0.0830          |
| 0.0824        | 1.62  | 190  | 0.0798          |
| 0.0871        | 1.71  | 200  | 0.0800          |
| 0.0861        | 1.79  | 210  | 0.0792          |
| 0.0844        | 1.88  | 220  | 0.0761          |
| 0.0802        | 1.96  | 230  | 0.0780          |
| 0.0691        | 2.05  | 240  | 0.0805          |
| 0.0602        | 2.13  | 250  | 0.0816          |
| 0.056         | 2.22  | 260  | 0.0802          |
| 0.0544        | 2.3   | 270  | 0.0834          |
| 0.0632        | 2.39  | 280  | 0.0769          |
| 0.0629        | 2.47  | 290  | 0.0735          |
| 0.0615        | 2.56  | 300  | 0.0739          |
| 0.0625        | 2.65  | 310  | 0.0756          |
| 0.056         | 2.73  | 320  | 0.0764          |
| 0.0586        | 2.82  | 330  | 0.0761          |
| 0.0576        | 2.9   | 340  | 0.0763          |
| 0.0582        | 2.99  | 350  | 0.0762          |


### Framework versions

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