---
license: apache-2.0
tags:
- generated_from_trainer
base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T
model-index:
- name: out
  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. -->

[<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)
# out

This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T](https://huggingface.co./TinyLlama/TinyLlama-1.1B-intermediate-step-1195k-token-2.5T) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9391

## 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: 2.5e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 6
- total_train_batch_size: 36
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 300
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.388         | 0.03  | 30   | 2.3495          |
| 2.3877        | 0.05  | 60   | 2.2353          |
| 2.1812        | 0.08  | 90   | 2.1786          |
| 2.1711        | 0.1   | 120  | 2.1453          |
| 2.098         | 0.13  | 150  | 2.1210          |
| 2.0884        | 0.15  | 180  | 2.1037          |
| 2.0129        | 0.18  | 210  | 2.0894          |
| 2.0921        | 0.2   | 240  | 2.0765          |
| 2.001         | 0.23  | 270  | 2.0648          |
| 2.0986        | 0.25  | 300  | 2.0550          |
| 2.0128        | 0.28  | 330  | 2.0458          |
| 2.1144        | 0.3   | 360  | 2.0385          |
| 2.0711        | 0.33  | 390  | 2.0308          |
| 1.9607        | 0.36  | 420  | 2.0239          |
| 1.9092        | 0.38  | 450  | 2.0179          |
| 2.1955        | 0.41  | 480  | 2.0121          |
| 2.0293        | 0.43  | 510  | 2.0063          |
| 2.0482        | 0.46  | 540  | 2.0017          |
| 2.0518        | 0.48  | 570  | 2.0036          |
| 1.9647        | 0.51  | 600  | 1.9984          |
| 2.0573        | 0.53  | 630  | 1.9938          |
| 1.9912        | 0.56  | 660  | 1.9879          |
| 1.9836        | 0.58  | 690  | 1.9866          |
| 1.9514        | 0.61  | 720  | 1.9834          |
| 1.9413        | 0.63  | 750  | 1.9792          |
| 1.9775        | 0.66  | 780  | 1.9726          |
| 1.9499        | 0.69  | 810  | 1.9690          |
| 2.0497        | 0.71  | 840  | 1.9663          |
| 2.0045        | 0.74  | 870  | 1.9636          |
| 2.0324        | 0.76  | 900  | 1.9605          |
| 1.9913        | 0.79  | 930  | 1.9574          |
| 1.9861        | 0.81  | 960  | 1.9553          |
| 1.8449        | 0.84  | 990  | 1.9527          |
| 1.9932        | 0.86  | 1020 | 1.9502          |
| 1.9845        | 0.89  | 1050 | 1.9485          |
| 2.0407        | 0.91  | 1080 | 1.9494          |
| 1.9496        | 0.94  | 1110 | 1.9448          |
| 1.9851        | 0.97  | 1140 | 1.9406          |
| 1.9856        | 0.99  | 1170 | 1.9391          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0

# [Open LLM Leaderboard Evaluation Results](https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/details_Dans-DiscountModels__TinyLlama-1.1B-FFT-Test2)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |35.53|
|AI2 Reasoning Challenge (25-Shot)|34.22|
|HellaSwag (10-Shot)              |57.96|
|MMLU (5-Shot)                    |25.54|
|TruthfulQA (0-shot)              |36.32|
|Winogrande (5-shot)              |58.80|
|GSM8k (5-shot)                   | 0.38|