---
license: other
base_model: yahma/llama-7b-hf
tags:
- generated_from_trainer
model-index:
- name: V0305B2
  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. -->

# V0305B2

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: 0.0894

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.352         | 0.09  | 10   | 2.3256          |
| 2.1754        | 0.17  | 20   | 1.8064          |
| 1.2745        | 0.26  | 30   | 0.6844          |
| 0.3789        | 0.34  | 40   | 0.1687          |
| 0.1587        | 0.43  | 50   | 0.1487          |
| 0.1563        | 0.51  | 60   | 0.1506          |
| 0.1505        | 0.6   | 70   | 0.1502          |
| 0.1525        | 0.68  | 80   | 0.1487          |
| 0.1481        | 0.77  | 90   | 0.1492          |
| 0.1504        | 0.85  | 100  | 0.1441          |
| 0.1501        | 0.94  | 110  | 0.1436          |
| 0.1439        | 1.02  | 120  | 0.1360          |
| 0.1411        | 1.11  | 130  | 0.1276          |
| 0.1349        | 1.19  | 140  | 0.1259          |
| 0.1345        | 1.28  | 150  | 0.1190          |
| 0.1299        | 1.37  | 160  | 0.1114          |
| 0.1275        | 1.45  | 170  | 0.1058          |
| 0.1159        | 1.54  | 180  | 0.1013          |
| 0.1189        | 1.62  | 190  | 0.0997          |
| 0.1203        | 1.71  | 200  | 0.1012          |
| 0.1177        | 1.79  | 210  | 0.0973          |
| 0.1144        | 1.88  | 220  | 0.0932          |
| 0.1128        | 1.96  | 230  | 0.0933          |
| 0.1084        | 2.05  | 240  | 0.0952          |
| 0.1081        | 2.13  | 250  | 0.0930          |
| 0.1037        | 2.22  | 260  | 0.0921          |
| 0.1011        | 2.3   | 270  | 0.0923          |
| 0.1072        | 2.39  | 280  | 0.0912          |
| 0.1058        | 2.47  | 290  | 0.0902          |
| 0.1107        | 2.56  | 300  | 0.0899          |
| 0.1066        | 2.65  | 310  | 0.0897          |
| 0.1091        | 2.73  | 320  | 0.0895          |
| 0.103         | 2.82  | 330  | 0.0893          |
| 0.1021        | 2.9   | 340  | 0.0893          |
| 0.103         | 2.99  | 350  | 0.0894          |


### Framework versions

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