---
base_model: Fischerboot/LLama3-Lexi-Aura-3Some-SLERP-SLERP-ql-merge
library_name: peft
tags:
- generated_from_trainer
model-index:
- name: outputs/newdataset-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)
<details><summary>See axolotl config</summary>

axolotl version: `0.4.1`
```yaml
base_model: Fischerboot/LLama3-Lexi-Aura-3Some-SLERP-SLERP-ql-merge
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: true
strict: false

chat_template: llama3
datasets:
  - path: Fischerboot/newnewdataset-sophie
    type: sharegpt
    conversation: llama3
dataset_prepared_path: last_run_prepared
val_set_size: 0.1
output_dir: ./outputs/newdataset-out

adapter: qlora
lora_model_dir:

sequence_len: 128
sample_packing: false
pad_to_sequence_len: true

lora_r: 1024
lora_alpha: 512
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
  - gate_proj
  - down_proj
  - up_proj
  - q_proj
  - v_proj
  - k_proj
  - o_proj

wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 8
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3

eval_sample_packing: false
warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  bos_token: "<|begin_of_text|>"
  eos_token: "<|end_of_text|>"
  pad_token: "<|end_of_text|>"

```

</details><br>

# outputs/newdataset-out

This model is a fine-tuned version of [Fischerboot/LLama3-Lexi-Aura-3Some-SLERP-SLERP-ql-merge](https://huggingface.co/Fischerboot/LLama3-Lexi-Aura-3Some-SLERP-SLERP-ql-merge) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2792

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

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 6.3499        | 0.0034 | 1    | 6.0611          |
| 1.4549        | 0.2526 | 74   | 1.8669          |
| 0.4942        | 0.5051 | 148  | 0.5161          |
| 0.5932        | 0.7577 | 222  | 1.2850          |
| 0.8581        | 1.0102 | 296  | 0.7266          |
| 1.1222        | 1.2628 | 370  | 0.3729          |
| 0.4354        | 1.5154 | 444  | 0.4699          |
| 0.6122        | 1.7679 | 518  | 0.6806          |
| 0.7419        | 2.0205 | 592  | 0.8912          |
| 2.7271        | 2.2730 | 666  | 1.2924          |
| 0.93          | 2.5256 | 740  | 0.8516          |
| 0.7029        | 2.7782 | 814  | 0.5884          |
| 0.5606        | 3.0307 | 888  | 0.5291          |
| 0.4365        | 3.2833 | 962  | 0.8004          |
| 0.2466        | 3.5358 | 1036 | 0.3922          |
| 0.6039        | 3.7884 | 1110 | 0.3917          |
| 0.1796        | 4.0410 | 1184 | 0.3216          |
| 0.3061        | 4.2935 | 1258 | 0.4309          |
| 0.7083        | 4.5461 | 1332 | 0.4010          |
| 0.3891        | 4.7986 | 1406 | 0.3268          |
| 0.331         | 5.0512 | 1480 | 0.3360          |
| 0.3014        | 5.3038 | 1554 | 0.2963          |
| 0.125         | 5.5563 | 1628 | 0.3096          |
| 0.3207        | 5.8089 | 1702 | 0.3020          |
| 0.2809        | 6.0614 | 1776 | 0.2849          |
| 1.5804        | 6.3140 | 1850 | 0.2801          |
| 0.4681        | 6.5666 | 1924 | 0.2826          |
| 0.2527        | 6.8191 | 1998 | 0.2793          |
| 0.2207        | 7.0717 | 2072 | 0.2787          |
| 0.2498        | 7.3242 | 2146 | 0.2799          |
| 0.1927        | 7.5768 | 2220 | 0.2798          |
| 0.415         | 7.8294 | 2294 | 0.2792          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.1.2+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1