---
library_name: peft
license: mit
base_model: fxmarty/tiny-random-GemmaForCausalLM
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 8a76346a-e5e1-4372-8a33-4ae45d89359b
  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
auto_resume_from_checkpoints: false
base_model: fxmarty/tiny-random-GemmaForCausalLM
bf16: false
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 95621c23f229fe74_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/95621c23f229fe74_train_data.json
  type:
    field_input: tools
    field_instruction: query
    field_output: answers
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 1000
eval_table_size: null
flash_attention: true
fp16: true
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: false
group_by_length: false
hub_model_id: error577/8a76346a-e5e1-4372-8a33-4ae45d89359b
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 128
lora_dropout: 0.05
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_steps: null
micro_batch_size: 2
mlflow_experiment_name: /tmp/95621c23f229fe74_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 10
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 1000
sequence_len: 512
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.005
wandb_entity: null
wandb_mode: online
wandb_name: e75973b3-c17e-44e4-b527-21c602afd6c4
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: e75973b3-c17e-44e4-b527-21c602afd6c4
warmup_steps: 300
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# 8a76346a-e5e1-4372-8a33-4ae45d89359b

This model is a fine-tuned version of [fxmarty/tiny-random-GemmaForCausalLM](https://huggingface.co/fxmarty/tiny-random-GemmaForCausalLM) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 12.1613

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 300
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 12.4513       | 0.0002 | 1     | 12.4418         |
| 12.2591       | 0.1637 | 1000  | 12.2520         |
| 12.2403       | 0.3275 | 2000  | 12.2224         |
| 12.2069       | 0.4912 | 3000  | 12.2032         |
| 12.1813       | 0.6550 | 4000  | 12.1945         |
| 12.2163       | 0.8187 | 5000  | 12.1882         |
| 12.1597       | 0.9825 | 6000  | 12.1822         |
| 12.2022       | 1.1462 | 7000  | 12.1761         |
| 12.2427       | 1.3100 | 8000  | 12.1720         |
| 12.1622       | 1.4737 | 9000  | 12.1691         |
| 12.2151       | 1.6375 | 10000 | 12.1676         |
| 12.18         | 1.8012 | 11000 | 12.1669         |
| 12.1537       | 1.9650 | 12000 | 12.1656         |
| 12.1634       | 2.1287 | 13000 | 12.1650         |
| 12.2148       | 2.2925 | 14000 | 12.1649         |
| 12.1868       | 2.4562 | 15000 | 12.1646         |
| 12.1903       | 2.6199 | 16000 | 12.1642         |
| 12.1781       | 2.7837 | 17000 | 12.1643         |
| 12.1894       | 2.9474 | 18000 | 12.1638         |
| 12.2065       | 3.1112 | 19000 | 12.1633         |
| 12.1887       | 3.2749 | 20000 | 12.1635         |
| 12.1549       | 3.4387 | 21000 | 12.1626         |
| 12.1719       | 3.6024 | 22000 | 12.1624         |
| 12.2151       | 3.7662 | 23000 | 12.1626         |
| 12.157        | 3.9299 | 24000 | 12.1629         |
| 12.1682       | 4.0937 | 25000 | 12.1619         |
| 12.1968       | 4.2574 | 26000 | 12.1619         |
| 12.1651       | 4.4212 | 27000 | 12.1617         |
| 12.168        | 4.5849 | 28000 | 12.1612         |
| 12.1713       | 4.7486 | 29000 | 12.1617         |
| 12.1767       | 4.9124 | 30000 | 12.1614         |
| 12.2027       | 5.0761 | 31000 | 12.1613         |


### Framework versions

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