---
library_name: transformers
base_model: Dans-DiscountModels/Meta-Llama-3.1-8B-ChatML
tags:
- generated_from_trainer
model-index:
- name: l3.1-8b-dans-instruct
  results: []
license: apache-2.0
---

<!-- 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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.4.1`
```yaml
base_model: Dans-DiscountModels/Meta-Llama-3.1-8B-ChatML
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

trust_remote_code:

# wandb configuration
wandb_project: l3.1-8b-dans-instruct
wandb_watch:
wandb_run_id:
wandb_log_model: 

# where to save the finished model to
output_dir: ./l3.1-8b-dans-instruct

# dataset settings (local or huggingface repo)
datasets:
  - path: PocketDoc/Dans-MemoryCore-CoreCurriculum-Small
    type: dan-chat
  - path: AquaV/Energetic-Materials-Sharegpt
    type: dan-chat
  - path: AquaV/Chemical-Biological-Safety-Applications-Sharegpt
    type: dan-chat
  - path: AquaV/US-Army-Survival-Sharegpt
    type: dan-chat
  - path: AquaV/Resistance-Sharegpt
    type: dan-chat
  - path: AquaV/Interrogation-Sharegpt
    type: dan-chat
  - path: AquaV/Multi-Environment-Operations-Sharegpt
    type: dan-chat
  - path: PocketDoc/Dans-Mathmaxx
    type: dan-chat
  - path: PocketDoc/Dans-Benchmaxx
    type: dan-chat
  - path: PocketDoc/Dans-Codemaxx
    type: dan-chat
  - path: PocketDoc/Dans-Taskmaxx
    type: dan-chat
  - path: PocketDoc/Dans-Toolmaxx
    type: dan-chat
  - path: PocketDoc/Dans-ASCIIMaxx-Wordart
    type: dan-chat
  - path: PocketDoc/Dans-Prosemaxx-Gutenberg
    type: dan-chat
  - path: PocketDoc/Dans-Prosemaxx-Cowriter
    type: dan-chat
  - path: PocketDoc/Dans-Prosemaxx-Cowriter-S
    type: dan-chat
  - path: PocketDoc/Dans-Prosemaxx-Adventure
    type: dan-chat
  - path: PocketDoc/DansTestYard
    type: completion

chat_template: chatml

plugins:
  - axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_swiglu: true
liger_fused_linear_cross_entropy: true

load_in_8bit: false
load_in_4bit: false
strict: false

dataset_prepared_path: ./l3.1-8b-dans-instruct-data
val_set_size: 0.01

sequence_len: 8192

sample_packing: true
eval_sample_packing: true

pad_to_sequence_len: true

gradient_checkpointing: true

gradient_accumulation_steps: 32
micro_batch_size: 1

num_epochs: 3

optimizer: adamw_torch

lr_scheduler: cosine
learning_rate: 0.0000015
cosine_min_lr_ratio: 

adam_beta1: 0.9
adam_beta2: 0.95
adam_epsilon: 0.00000001
weight_decay: 0.05

train_on_inputs: false
group_by_length: true

bf16: true
fp16: false
tf32: false

early_stopping_patience:

resume_from_checkpoint: 
auto_resume_from_checkpoints: 

local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_ratio: 0.1
evals_per_epoch: 10
eval_table_size:
eval_max_new_tokens:
saves_per_epoch: 2

debug: false

deepspeed:
fsdp:
fsdp_config:

special_tokens:
  pad_token: <|finetune_right_pad_id|>
  eos_token: <|im_end|>
```

</details><br>

# l3.1-8b-dans-instruct

This model is a fine-tuned version of [Dans-DiscountModels/Meta-Llama-3.1-8B-ChatML](https://huggingface.co/Dans-DiscountModels/Meta-Llama-3.1-8B-ChatML) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5811

## 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: 1.5e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 97
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.7656        | 0.0031 | 1    | 1.7463          |
| 1.7434        | 0.1009 | 33   | 1.7351          |
| 1.6519        | 0.2018 | 66   | 1.6830          |
| 1.679         | 0.3027 | 99   | 1.6342          |
| 1.6336        | 0.4036 | 132  | 1.6168          |
| 1.5928        | 0.5044 | 165  | 1.6063          |
| 1.6581        | 0.6053 | 198  | 1.5996          |
| 1.646         | 0.7062 | 231  | 1.5957          |
| 1.6064        | 0.8071 | 264  | 1.5924          |
| 1.5328        | 0.9080 | 297  | 1.5899          |
| 1.6039        | 1.0069 | 330  | 1.5881          |
| 1.6226        | 1.1080 | 363  | 1.5867          |
| 1.4879        | 1.2090 | 396  | 1.5855          |
| 1.6646        | 1.3101 | 429  | 1.5844          |
| 1.5874        | 1.4112 | 462  | 1.5836          |
| 1.4901        | 1.5123 | 495  | 1.5830          |
| 1.6148        | 1.6133 | 528  | 1.5825          |
| 1.3064        | 1.7144 | 561  | 1.5822          |
| 1.4952        | 1.8155 | 594  | 1.5817          |
| 1.6338        | 1.9165 | 627  | 1.5816          |
| 1.7102        | 2.0156 | 660  | 1.5815          |
| 1.6408        | 2.1165 | 693  | 1.5813          |
| 1.3856        | 2.2175 | 726  | 1.5813          |
| 1.537         | 2.3184 | 759  | 1.5813          |
| 1.6205        | 2.4194 | 792  | 1.5812          |
| 1.7095        | 2.5203 | 825  | 1.5811          |
| 1.4987        | 2.6213 | 858  | 1.5811          |
| 1.6141        | 2.7222 | 891  | 1.5811          |
| 1.5662        | 2.8232 | 924  | 1.5811          |
| 1.5975        | 2.9241 | 957  | 1.5811          |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1