---
base_model: NousResearch/Llama-2-7b-hf
tags:
- generated_from_trainer
model-index:
- name: classifier-7b-v9
  results: []
---

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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
# classifier-7b-v9

This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8197

## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.171         | 0.02  | 20   | 2.1160          |
| 1.881         | 0.04  | 40   | 1.9814          |
| 2.0141        | 0.06  | 60   | 1.9357          |
| 1.9386        | 0.08  | 80   | 1.9156          |
| 1.9899        | 0.1   | 100  | 1.9032          |
| 1.9022        | 0.11  | 120  | 1.8964          |
| 1.9176        | 0.13  | 140  | 1.8880          |
| 1.9431        | 0.15  | 160  | 1.8827          |
| 1.8847        | 0.17  | 180  | 1.8772          |
| 1.8158        | 0.19  | 200  | 1.8740          |
| 1.851         | 0.21  | 220  | 1.8711          |
| 1.8173        | 0.23  | 240  | 1.8678          |
| 1.7902        | 0.25  | 260  | 1.8639          |
| 1.8507        | 0.27  | 280  | 1.8600          |
| 1.8749        | 0.29  | 300  | 1.8582          |
| 1.9203        | 0.3   | 320  | 1.8543          |
| 1.8876        | 0.32  | 340  | 1.8518          |
| 1.8918        | 0.34  | 360  | 1.8510          |
| 1.9568        | 0.36  | 380  | 1.8482          |
| 1.7887        | 0.38  | 400  | 1.8489          |
| 1.9188        | 0.4   | 420  | 1.8451          |
| 1.855         | 0.42  | 440  | 1.8434          |
| 1.94          | 0.44  | 460  | 1.8421          |
| 1.7969        | 0.46  | 480  | 1.8399          |
| 1.875         | 0.48  | 500  | 1.8384          |
| 1.8493        | 0.5   | 520  | 1.8383          |
| 1.8048        | 0.51  | 540  | 1.8370          |
| 1.9077        | 0.53  | 560  | 1.8352          |
| 1.804         | 0.55  | 580  | 1.8327          |
| 1.8623        | 0.57  | 600  | 1.8315          |
| 1.8156        | 0.59  | 620  | 1.8312          |
| 1.8639        | 0.61  | 640  | 1.8306          |
| 1.909         | 0.63  | 660  | 1.8292          |
| 1.8636        | 0.65  | 680  | 1.8290          |
| 1.7888        | 0.67  | 700  | 1.8270          |
| 1.7797        | 0.69  | 720  | 1.8259          |
| 1.8014        | 0.7   | 740  | 1.8248          |
| 1.7313        | 0.72  | 760  | 1.8240          |
| 1.8429        | 0.74  | 780  | 1.8235          |
| 1.814         | 0.76  | 800  | 1.8235          |
| 1.7861        | 0.78  | 820  | 1.8221          |
| 1.8515        | 0.8   | 840  | 1.8212          |
| 1.8432        | 0.82  | 860  | 1.8209          |
| 1.8018        | 0.84  | 880  | 1.8204          |
| 1.864         | 0.86  | 900  | 1.8203          |
| 1.7234        | 0.88  | 920  | 1.8201          |
| 1.84          | 0.89  | 940  | 1.8198          |
| 1.8721        | 0.91  | 960  | 1.8199          |
| 1.7822        | 0.93  | 980  | 1.8198          |
| 1.8464        | 0.95  | 1000 | 1.8197          |
| 1.7454        | 0.97  | 1020 | 1.8197          |
| 1.7434        | 0.99  | 1040 | 1.8197          |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1