---
library_name: peft
license: apache-2.0
base_model: EleutherAI/pythia-410m-deduped
tags:
- axolotl
- generated_from_trainer
model-index:
- name: bf58c716-f1ab-4447-897b-55ade88ff479
  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
adapter: lora
base_model: EleutherAI/pythia-410m-deduped
batch_size: 8
bf16: true
chat_template: tokenizer_default_fallback_alpaca
datasets:
- data_files:
  - 7b17ba91d0356ec9_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/7b17ba91d0356ec9_train_data.json
  type:
    field_instruction: prompt
    field_output: completion
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
early_stopping_patience: 3
eval_steps: 50
flash_attention: true
gpu_memory_limit: 80GiB
gradient_checkpointing: true
group_by_length: true
hub_model_id: willtensora/bf58c716-f1ab-4447-897b-55ade88ff479
hub_strategy: checkpoint
learning_rate: 0.0002
logging_steps: 10
lora_alpha: 256
lora_dropout: 0.1
lora_r: 128
lora_target_linear: true
lr_scheduler: cosine
micro_batch_size: 1
model_type: AutoModelForCausalLM
num_epochs: 100
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resize_token_embeddings_to_32x: false
sample_packing: false
save_steps: 50
sequence_len: 2048
special_tokens:
  pad_token: <|endoftext|>
tokenizer_type: GPTNeoXTokenizerFast
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.1
wandb_entity: ''
wandb_mode: online
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: default
warmup_ratio: 0.05
xformers_attention: true

```

</details><br>

# bf58c716-f1ab-4447-897b-55ade88ff479

This model is a fine-tuned version of [EleutherAI/pythia-410m-deduped](https://huggingface.co/EleutherAI/pythia-410m-deduped) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4376

## 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- total_eval_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 153
- num_epochs: 100

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0041 | 1    | 1.8043          |
| 1.4581        | 0.2033 | 50   | 1.4781          |
| 1.7801        | 0.4065 | 100  | 1.7743          |
| 1.6691        | 0.6098 | 150  | 1.7577          |
| 2.3973        | 0.8130 | 200  | 2.4376          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1