---
license: other
base_model: yahma/llama-7b-hf
tags:
- generated_from_trainer
model-index:
- name: V0305O2
  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. -->

# V0305O2

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: 0.1482

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 3.7252        | 0.09  | 10   | 0.2911          |
| 0.1739        | 0.17  | 20   | 0.1561          |
| 0.1571        | 0.26  | 30   | 0.1529          |
| 0.1516        | 0.34  | 40   | 0.1509          |
| 0.1514        | 0.43  | 50   | 0.1507          |
| 0.1564        | 0.51  | 60   | 0.1511          |
| 0.1519        | 0.6   | 70   | 0.1509          |
| 0.1534        | 0.68  | 80   | 0.1493          |
| 0.1492        | 0.77  | 90   | 0.1490          |
| 0.1527        | 0.85  | 100  | 0.1498          |
| 0.1543        | 0.94  | 110  | 0.1491          |
| 0.1504        | 1.02  | 120  | 0.1506          |
| 0.1536        | 1.11  | 130  | 0.1498          |
| 0.1493        | 1.19  | 140  | 0.1504          |
| 0.1526        | 1.28  | 150  | 0.1492          |
| 0.1529        | 1.37  | 160  | 0.1500          |
| 0.1519        | 1.45  | 170  | 0.1490          |
| 0.1491        | 1.54  | 180  | 0.1495          |
| 0.1539        | 1.62  | 190  | 0.1491          |
| 0.153         | 1.71  | 200  | 0.1485          |
| 0.1514        | 1.79  | 210  | 0.1492          |
| 0.154         | 1.88  | 220  | 0.1501          |
| 0.1562        | 1.96  | 230  | 0.1490          |
| 0.1511        | 2.05  | 240  | 0.1491          |
| 0.154         | 2.13  | 250  | 0.1484          |
| 0.1505        | 2.22  | 260  | 0.1489          |
| 0.1492        | 2.3   | 270  | 0.1488          |
| 0.1546        | 2.39  | 280  | 0.1478          |
| 0.1528        | 2.47  | 290  | 0.1476          |
| 0.1516        | 2.56  | 300  | 0.1479          |
| 0.1508        | 2.65  | 310  | 0.1482          |
| 0.1523        | 2.73  | 320  | 0.1482          |
| 0.1501        | 2.82  | 330  | 0.1483          |
| 0.1498        | 2.9   | 340  | 0.1483          |
| 0.151         | 2.99  | 350  | 0.1482          |


### Framework versions

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