---
library_name: peft
license: apache-2.0
base_model: EleutherAI/pythia-160m
tags:
- axolotl
- generated_from_trainer
model-index:
- name: e1137da5-d393-4ed5-93a7-2227cd97c54c
  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-160m
bf16: auto
chat_template: llama3
dataloader_num_workers: 12
dataset_prepared_path: null
datasets:
- data_files:
  - 3cd429aa92a7467a_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/3cd429aa92a7467a_train_data.json
  type:
    field_instruction: instruction
    field_output: response
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
device_map: auto
do_eval: true
early_stopping_patience: 3
eval_batch_size: 8
eval_max_new_tokens: 128
eval_steps: 150
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: true
group_by_length: true
hub_model_id: nttx/e1137da5-d393-4ed5-93a7-2227cd97c54c
hub_repo: null
hub_strategy: end
hub_token: null
learning_rate: 3e-5
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 10
lora_alpha: 128
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_memory:
  0: 75GB
max_steps: 1500
micro_batch_size: 8
mlflow_experiment_name: /tmp/3cd429aa92a7467a_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 15
optim_args:
  adam_beta1: 0.9
  adam_beta2: 0.999
  adam_epsilon: 1e-8
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: false
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 150
saves_per_epoch: null
sequence_len: 1024
special_tokens:
  pad_token: <|endoftext|>
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 62c135b7-8472-4121-bd91-09a2c16c46be
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 62c135b7-8472-4121-bd91-09a2c16c46be
warmup_steps: 50
weight_decay: 0.1
xformers_attention: null

```

</details><br>

# e1137da5-d393-4ed5-93a7-2227cd97c54c

This model is a fine-tuned version of [EleutherAI/pythia-160m](https://huggingface.co/EleutherAI/pythia-160m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6498

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.999,adam_epsilon=1e-8
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 1500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0004 | 1    | 2.8632          |
| 7.6309        | 0.0594 | 150  | 2.7300          |
| 7.6888        | 0.1188 | 300  | 2.7534          |
| 7.1831        | 0.1782 | 450  | 2.7060          |
| 7.3785        | 0.2376 | 600  | 2.7084          |
| 7.351         | 0.2970 | 750  | 2.6926          |
| 6.9755        | 0.3564 | 900  | 2.6618          |
| 7.4723        | 0.4158 | 1050 | 2.6380          |
| 6.9795        | 0.4752 | 1200 | 2.6514          |
| 6.8663        | 0.5345 | 1350 | 2.6419          |
| 6.9371        | 0.5939 | 1500 | 2.6498          |


### Framework versions

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