---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
model-index:
- name: llama_finetune_mc_20_cot
  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. -->

# llama_finetune_mc_20_cot

This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0293

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.9129        | 1.0   | 70   | 1.6726          |
| 0.2315        | 2.0   | 140  | 2.3392          |
| 0.1771        | 3.0   | 210  | 2.4929          |
| 0.1428        | 4.0   | 280  | 2.6548          |
| 0.1106        | 5.0   | 350  | 2.6539          |
| 0.0592        | 6.0   | 420  | 2.8574          |
| 0.051         | 7.0   | 490  | 3.0477          |
| 0.0568        | 8.0   | 560  | 3.1988          |
| 0.0309        | 9.0   | 630  | 3.2646          |
| 0.0235        | 10.0  | 700  | 3.4138          |
| 0.0243        | 11.0  | 770  | 3.3431          |
| 0.0259        | 12.0  | 840  | 3.5628          |
| 0.0232        | 13.0  | 910  | 3.6910          |
| 0.0221        | 14.0  | 980  | 3.6820          |
| 0.0202        | 15.0  | 1050 | 3.8640          |
| 0.0181        | 16.0  | 1120 | 3.9228          |
| 0.0191        | 17.0  | 1190 | 3.9716          |
| 0.0184        | 18.0  | 1260 | 4.0096          |
| 0.0186        | 19.0  | 1330 | 4.0225          |
| 0.0165        | 20.0  | 1400 | 4.0293          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.13.1
- Tokenizers 0.14.1