---
library_name: peft
license: apache-2.0
base_model: EleutherAI/pythia-410m-deduped
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 965564f6-7c31-434d-ab93-3155a0cb53be
  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
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - ccd86841471aa985_train_data.json
  ds_type: json
  field: prompt
  path: /workspace/input_data/
  split: train
  type: completion
ddp_find_unused_parameters: false
debug: null
deepspeed: null
early_stopping_patience: null
ema_decay: 0.999
ema_update_after_step: 100
eval_max_new_tokens: 256
eval_table_size: null
evals_per_epoch: 4
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: true
gradient_clipping: 1.0
greater_is_better: false
group_by_length: false
hub_model_id: CheapsetZero/965564f6-7c31-434d-ab93-3155a0cb53be
learning_rate: 0.0001
load_best_model_at_end: true
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_nan_inf_filter: true
logging_steps: 1
lora_alpha: 256
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 128
lora_target_linear: true
lr_scheduler: cosine
max_steps: 8640
metric_for_best_model: eval_loss
micro_batch_size: 8
min_lr: 1.0e-05
mlflow_experiment_name: /tmp/ccd86841471aa985_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
reward_model_sampling_temperature: 0.7
s2_attention: null
sample_packing: false
save_total_limit: 3
saves_per_epoch: 4
sequence_len: 1024
special_tokens:
  pad_token: <|endoftext|>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trl:
  beta: 0.015
  max_completion_length: 1024
  num_generations: 16
  reward_funcs:
  - rewards_331f1bc8-fd1a-45f2-8342-6a1255fa8cb4.reward_low_readability
  - rewards_331f1bc8-fd1a-45f2-8342-6a1255fa8cb4.reward_specific_char_count
  - rewards_331f1bc8-fd1a-45f2-8342-6a1255fa8cb4.reward_reasoning_keywords
  - rewards_331f1bc8-fd1a-45f2-8342-6a1255fa8cb4.reward_high_readability
  reward_weights:
  - 3.87207489867356
  - 0.937376822051259
  - 7.290092942424822
  - 2.502552982256603
  use_vllm: false
trust_remote_code: true
use_ema: true
use_peft: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: offline
wandb_name: 331f1bc8-fd1a-45f2-8342-6a1255fa8cb4
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 331f1bc8-fd1a-45f2-8342-6a1255fa8cb4
warmup_steps: 864
weight_decay: 0.01
xformers_attention: null

```

</details><br>

# 965564f6-7c31-434d-ab93-3155a0cb53be

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: 1.4671

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 864
- training_steps: 1202

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 7.3325        | 0.0025 | 1    | 3.7155          |
| 3.1448        | 0.2522 | 101  | 1.6412          |
| 3.0834        | 0.5044 | 202  | 1.4707          |
| 2.5995        | 0.7566 | 303  | 1.4762          |
| 3.2809        | 1.0087 | 404  | 1.5102          |
| 2.8995        | 1.2609 | 505  | 1.4836          |
| 2.7854        | 1.5131 | 606  | 1.5506          |
| 3.2836        | 1.7653 | 707  | 1.5887          |
| 2.6248        | 2.0175 | 808  | 1.4920          |
| 2.8987        | 2.2697 | 909  | 1.5846          |
| 2.946         | 2.5218 | 1010 | 1.5297          |
| 2.4191        | 2.7740 | 1111 | 1.4671          |


### Framework versions

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