---
library_name: peft
license: apache-2.0
base_model: EleutherAI/pythia-160m
tags:
- axolotl
- generated_from_trainer
model-index:
- name: d0c65863-45bc-4f92-9929-f5e665eff8af
  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: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - cb60d6a9b4ff3d3a_train_data.json
  ds_type: json
  field: query
  path: /workspace/input_data/cb60d6a9b4ff3d3a_train_data.json
  type: completion
debug: null
deepspeed: null
device_map: auto
early_stopping_patience: 3
ema_decay: 0.9992
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
greater_is_better: false
group_by_length: false
hub_model_id: JoshMe1/d0c65863-45bc-4f92-9929-f5e665eff8af
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0001
load_best_model_at_end: true
load_in_4bit: false
load_in_8bit: true
local_rank: null
logging_steps: 10
lora_alpha: 256
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: reduce_lr_on_plateau
lr_scheduler_factor: 0.5
lr_scheduler_patience: 2
max_memory:
  0: 130GB
max_steps: 500
metric_for_best_model: eval_loss
micro_batch_size: 4
mlflow_experiment_name: /tmp/cb60d6a9b4ff3d3a_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_hf
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 100
saves_per_epoch: null
sequence_len: 2048
special_tokens:
  pad_token: <|endoftext|>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
use_ema: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 72033cbb-9607-4a6e-a252-62a89a2f99d4
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 72033cbb-9607-4a6e-a252-62a89a2f99d4
warmup_steps: 200
weight_decay: 0.01
xformers_attention: null

```

</details><br>

# d0c65863-45bc-4f92-9929-f5e665eff8af

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: 4.9802

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_HF with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: reduce_lr_on_plateau
- lr_scheduler_warmup_steps: 200
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0001 | 1    | 4.8533          |
| 21.894        | 0.0085 | 100  | 5.8594          |
| 22.1192       | 0.0169 | 200  | 5.7406          |
| 20.4868       | 0.0254 | 300  | 5.1533          |
| 20.419        | 0.0339 | 400  | 5.1123          |
| 20.3705       | 0.0423 | 500  | 4.9802          |


### Framework versions

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