---
base_model: EleutherAI/pythia-1.4b-deduped
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: outputs/lora-alpaca-pythia
  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/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: EleutherAI/pythia-1.4b-deduped
load_in_8bit: true
datasets:
  - path: teknium/GPT4-LLM-Cleaned
    type: alpaca
dataset_prepared_path:
val_set_size: 0.05
adapter: lora
lora_model_dir:
sequence_len: 512
lora_r: 16
lora_alpha: 32
lora_dropout: 0.05
lora_target_modules:
  - query_key_value
  - dense
  - dense_h_to_4h
  - dense_4h_to_h
lora_target_linear:
lora_fan_in_fan_out: true  # pythia/GPTNeoX lora specific
wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
output_dir: ./outputs/lora-alpaca-pythia
gradient_accumulation_steps: 1
micro_batch_size: 4
num_epochs: 4
learning_rate: 0.00001
train_on_inputs: false
group_by_length: false
bf16: auto
tf32: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
weight_decay: 0.1
evals_per_epoch: 4
logging_steps: 1
push_to_hub: tommyp111/pythia-1.4b-deduped-alpaca-lora
wandb_project: pythia-alpaca-lora
wandb_name: pythia-1.4b


```

</details><br>

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/tompollak/pythia-alpaca-lora/runs/oyhginqx)
# outputs/lora-alpaca-pythia

This model is a fine-tuned version of [EleutherAI/pythia-1.4b-deduped](https://huggingface.co/EleutherAI/pythia-1.4b-deduped) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2444

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 1.5363        | 0.0001 | 1     | 2.6674          |
| 1.2474        | 0.25   | 3190  | 1.4167          |
| 1.3556        | 0.5    | 6380  | 1.3586          |
| 1.2912        | 0.75   | 9570  | 1.3302          |
| 1.2149        | 1.0    | 12760 | 1.3089          |
| 1.6017        | 1.25   | 15950 | 1.2917          |
| 1.1827        | 1.5    | 19140 | 1.2827          |
| 0.9565        | 1.75   | 22330 | 1.2739          |
| 1.2363        | 2.0    | 25520 | 1.2674          |
| 1.3477        | 2.25   | 28710 | 1.2596          |
| 1.6589        | 2.5    | 31900 | 1.2571          |
| 1.1538        | 2.75   | 35090 | 1.2530          |
| 1.5866        | 3.0    | 38280 | 1.2473          |
| 1.0768        | 3.25   | 41470 | 1.2464          |
| 1.4019        | 3.5    | 44660 | 1.2452          |
| 1.1724        | 3.75   | 47850 | 1.2434          |
| 1.3227        | 4.0    | 51040 | 1.2444          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.43.1
- Pytorch 2.3.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1