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tomaszki
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model-21

PEFT
Safetensors
llama
axolotl
Generated from Trainer
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model-21
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---
library_name: peft
tags:
- axolotl
- generated_from_trainer
base_model: tomaszki/nous-thirty-four-0
model-index:
- name: model-21
  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: `0.4.0`
```yaml
base_model: tomaszki/nous-thirty-four-0
model_type: LlamaForCausalLM
is_llama_derived_model: true
hub_model_id: model-21

load_in_8bit: false
load_in_4bit: false
strict: false


datasets:
  - path: tomaszki/nous-finetune-axolotl-completion-21
val_set_size: 0.0
output_dir: model-21

sequence_len: 512
sample_packing: false

wandb_project: axolotl
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

adapter: lora
lora_model_dir:
lora_r: 32
lora_alpha: 16
lora_dropout: 0.00
lora_target_linear: true
lora_fan_in_fan_out:

gradient_accumulation_steps: 1
micro_batch_size: 12
num_epochs: 2
optimizer: adamw_hf
lr_scheduler: cosine
learning_rate: 0.00001
cosine_min_lr_ratio: 0.5

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

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

warmup_steps: 0
saves_per_epoch: 1
debug:
deepspeed: #deepspeed_configs/zero2.json
weight_decay: 0.01
fsdp:
fsdp_config:
special_tokens:

```

</details><br>

# model-21

This model is a fine-tuned version of [tomaszki/nous-thirty-four-0](https://huggingface.co/tomaszki/nous-thirty-four-0) on an unknown dataset.

## 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: 1e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 2

### Training results



### Framework versions

- PEFT 0.8.2
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu118
- Datasets 2.17.1
- Tokenizers 0.15.0