---
library_name: peft
license: apache-2.0
base_model: echarlaix/tiny-random-PhiForCausalLM
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 56fde327-537c-4d7d-8a47-5553a75fd430
  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: echarlaix/tiny-random-PhiForCausalLM
bf16: auto
chat_template: llama3
dataset_prepared_path: null
dataset_processes: 
datasets:
- data_files:
  - df4145ffec439e54_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/df4145ffec439e54_train_data.json
  type:
    field_instruction: text
    field_output: text_ja
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 150
eval_table_size: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 1
gradient_checkpointing: true
group_by_length: false
hub_model_id: error577/56fde327-537c-4d7d-8a47-5553a75fd430
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: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: null
micro_batch_size: 512
mlflow_experiment_name: /tmp/df4145ffec439e54_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 50
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 150
sequence_len: 512
special_tokens:
  pad_token: <|endoftext|>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.5
wandb_entity: null
wandb_mode: online
wandb_name: c30de9d5-9d24-44e1-9b62-deb3229d1fce
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: c30de9d5-9d24-44e1-9b62-deb3229d1fce
warmup_steps: 30
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# 56fde327-537c-4d7d-8a47-5553a75fd430

This model is a fine-tuned version of [echarlaix/tiny-random-PhiForCausalLM](https://huggingface.co/echarlaix/tiny-random-PhiForCausalLM) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 6.6156

## 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: 512
- eval_batch_size: 512
- seed: 42
- 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: 30
- num_epochs: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 6.9448        | 0.0116  | 1    | 6.9446          |
| 6.6809        | 1.7442  | 150  | 6.6820          |
| 6.6655        | 3.4884  | 300  | 6.6633          |
| 6.6563        | 5.2326  | 450  | 6.6522          |
| 6.649         | 6.9767  | 600  | 6.6462          |
| 6.6442        | 8.7209  | 750  | 6.6431          |
| 6.6415        | 10.4651 | 900  | 6.6377          |
| 6.6357        | 12.2093 | 1050 | 6.6346          |
| 6.6334        | 13.9535 | 1200 | 6.6311          |
| 6.6309        | 15.6977 | 1350 | 6.6292          |
| 6.6386        | 17.4419 | 1500 | 6.6275          |
| 6.6273        | 19.1860 | 1650 | 6.6248          |
| 6.627         | 20.9302 | 1800 | 6.6227          |
| 6.6243        | 22.6744 | 1950 | 6.6207          |
| 6.6252        | 24.4186 | 2100 | 6.6195          |
| 6.6204        | 26.1628 | 2250 | 6.6187          |
| 6.6222        | 27.9070 | 2400 | 6.6182          |
| 6.6231        | 29.6512 | 2550 | 6.6176          |
| 6.6196        | 31.3953 | 2700 | 6.6171          |
| 6.6161        | 33.1395 | 2850 | 6.6168          |
| 6.6213        | 34.8837 | 3000 | 6.6165          |
| 6.6209        | 36.6279 | 3150 | 6.6162          |
| 6.6176        | 38.3721 | 3300 | 6.6160          |
| 6.6219        | 40.1163 | 3450 | 6.6158          |
| 6.619         | 41.8605 | 3600 | 6.6157          |
| 6.6143        | 43.6047 | 3750 | 6.6156          |
| 6.6199        | 45.3488 | 3900 | 6.6156          |
| 6.6195        | 47.0930 | 4050 | 6.6156          |
| 6.6185        | 48.8372 | 4200 | 6.6156          |


### Framework versions

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