Downloads · 30 days
8
5% of all-time downloads
pythia-1.4b-deduped-alpaca-lora
tommyp111/pythia-1.4b-deduped-alpaca-lora
pythia-1.4b-deduped-alpaca-lora is a machine learning model from tommyp111. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
172
Public
Repo size
655 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.pt403 MB · 59%
At a glance
- Library
- peft
- License
- apache-2.0
- Model type
- gpt_neox
- Access
- Public
- Created
- Sep 13, 2024
- Updated
- Sep 13, 2024
- SHA
- 944f94c4
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
<details><summary>See axolotl config</summary>
axolotl version: 0.4.1
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
outputs/lora-alpaca-pythia
This model is a fine-tuned version of 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
- Library
- peft
- Type
- gpt_neox
- License
- apache-2.0
- Created
- Sep 13, 2024
- Updated
- Sep 13, 2024