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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
model-index:
- name: qlora-out
results: []
datasets:
- totally-not-an-llm/ZorgonChat
---
[<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: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
model_type: LlamaForCausalLM
tokenizer_type: LlamaTokenizer
load_in_8bit: false
load_in_4bit: true
strict: false
datasets:
- path: totally-not-an-llm/ZorgonChat
type: alpaca
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./qlora-out
adapter: qlora
lora_model_dir:
sequence_len: 4096
sample_packing: false
pad_to_sequence_len: true
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_modules:
lora_target_linear: true
lora_fan_in_fan_out:
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 4
optimizer: paged_adamw_32bit
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
warmup_steps: 10
evals_per_epoch: 4
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
```
</details><br>
# qlora-out
This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T) on the [ZorgonChat](https://huggingface.co/datasets/totally-not-an-llm/ZorgonChat) dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3466
## Model description
Trained on a dataset of "alien language" chats to see if it will learn to talk in english. Prompt format is:
```
You are a helpful assistant., respond in Language: English
### Instruction:
{prompt}
### Response:
```
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.9295 | 0.03 | 1 | 3.9073 |
| 3.5364 | 0.25 | 8 | 3.6199 |
| 3.263 | 0.5 | 16 | 3.1821 |
| 2.798 | 0.75 | 24 | 2.8962 |
| 2.7787 | 1.0 | 32 | 2.6773 |
| 2.5959 | 1.25 | 40 | 2.5506 |
| 2.4793 | 1.5 | 48 | 2.4955 |
| 2.5221 | 1.75 | 56 | 2.4613 |
| 2.4384 | 2.0 | 64 | 2.4055 |
| 2.295 | 2.25 | 72 | 2.3923 |
| 2.3943 | 2.5 | 80 | 2.3862 |
| 2.2398 | 2.75 | 88 | 2.3605 |
| 2.2693 | 3.0 | 96 | 2.3526 |
| 2.425 | 3.25 | 104 | 2.3471 |
| 2.2857 | 3.5 | 112 | 2.3468 |
| 2.2448 | 3.75 | 120 | 2.3451 |
| 2.1836 | 4.0 | 128 | 2.3466 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.0.dev0
- Pytorch 2.1.2+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0 |