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---
library_name: peft
tags:
- axolotl
- generated_from_trainer
base_model: EleutherAI/pythia-14m
model-index:
- name: 6cc0d0ea-35bf-40f0-bc75-67f500f02e10
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: `0.4.1`
```yaml
adapter: lora
base_model: EleutherAI/pythia-14m
bf16: auto
dataset_prepared_path: null
datasets:
- data_files:
- 277437aee072aff2_train_data.json
ds_type: json
format: custom
path: 277437aee072aff2_train_data.json
type:
field: null
field_input: null
field_instruction: title
field_output: text
field_system: null
format: null
no_input_format: null
system_format: '{system}'
system_prompt: ''
early_stopping_patience: null
evals_per_epoch: 3
gradient_accumulation_steps: 1
group_by_length: false
hub_model_id: taopanda/6cc0d0ea-35bf-40f0-bc75-67f500f02e10
learning_rate: 1.0e-05
load_in_8bit: true
local_rank: null
logging_steps: 1
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: true
lora_model_dir: null
lora_r: 16
lora_target_linear: null
lora_target_modules:
- query_key_value
micro_batch_size: 4
num_epochs: 1
output_dir: ./outputs/lora-alpaca-pythia/taopanda-2_8dcf0032-e46f-4576-a8d2-bc4808352225
resume_from_checkpoint: null
seed: 20217
sequence_len: 512
special_tokens:
pad_token: <|endoftext|>
tf32: true
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: fatcat87-taopanda
wandb_log_model: null
wandb_mode: online
wandb_name: taopanda-2_8dcf0032-e46f-4576-a8d2-bc4808352225
wandb_project: subnet56
wandb_runid: taopanda-2_8dcf0032-e46f-4576-a8d2-bc4808352225
wandb_watch: null
weight_decay: 0.1
```
</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/fatcat87-taopanda/subnet56/runs/52g80p2l)
# 6cc0d0ea-35bf-40f0-bc75-67f500f02e10
This model is a fine-tuned version of [EleutherAI/pythia-14m](https://huggingface.co/EleutherAI/pythia-14m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 5.3335
## 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: 20217
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 5.2045 | 0.0000 | 1 | 5.5794 |
| 5.6734 | 0.3334 | 10407 | 5.2100 |
| 4.6502 | 0.6667 | 20814 | 5.3335 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |