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pythia-125m-gpt4-llm-cleaned
jtatman/pythia-125m-gpt4-llm-cleaned
pythia-125m-gpt4-llm-cleaned is a machine learning model from jtatman. 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. --
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At a glance
- Library
- peft
- License
- apache-2.0
- Model type
- gpt_neox
- Access
- Public
- Created
- Jun 22, 2024
- Updated
- Jun 22, 2024
- SHA
- 3a80cbf6
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-125m-deduped
load_in_8bit: false
datasets:
- path: jtatman/storywriting_combined_instruct
type: alpaca
dataset_prepared_path: ds-storytelling
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
lora_target_linear: true
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-125m
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: false
float16: true
gpu_memory_limit: 8GiB
hub_model_id: jtatman/pythia-125m-gpt4-llm-cleaned
lora_on_cpu: false
early_stopping_patience:
resume_from_checkpoint:
local_rank:
weight_decay: 0.1
evals_per_epoch: 4
logging_steps: 1
pythia-125m-gpt4-llm-cleaned
This model is a fine-tuned version of EleutherAI/pythia-125m-deduped on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.6093
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 |
|---|---|---|---|
| 3.1847 | 0.0008 | 1 | 2.7080 |
| 2.8391 | 0.2504 | 326 | 2.6464 |
| 2.9722 | 0.5008 | 652 | 2.6312 |
| 2.9904 | 0.7512 | 978 | 2.6245 |
| 3.1704 | 1.0015 | 1304 | 2.6179 |
| 3.1108 | 1.2519 | 1630 | 2.6155 |
| 2.9321 | 1.5023 | 1956 | 2.6143 |
| 3.0499 | 1.7527 | 2282 | 2.6113 |
| 2.9776 | 2.0031 | 2608 | 2.6102 |
| 2.7773 | 2.2535 | 2934 | 2.6102 |
| 3.5383 | 2.5038 | 3260 | 2.6106 |
| 2.8105 | 2.7542 | 3586 | 2.6106 |
| 3.0778 | 3.0046 | 3912 | 2.6115 |
| 2.9706 | 3.2550 | 4238 | 2.6096 |
| 2.7671 | 3.5054 | 4564 | 2.6100 |
| 3.3049 | 3.7558 | 4890 | 2.6093 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Library
- peft
- Type
- gpt_neox
- License
- apache-2.0
- Created
- Jun 22, 2024
- Updated
- Jun 22, 2024