---
library_name: peft
license: apache-2.0
base_model: echarlaix/tiny-random-mistral
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 9db6cbba-2a7f-4aa3-98b7-fa898ca8f99a
  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: echarlaix/tiny-random-mistral
bf16: true
chat_template: llama3
dataloader_num_workers: 24
dataset_prepared_path: null
datasets:
- data_files:
  - 757dd5c118de8497_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/757dd5c118de8497_train_data.json
  type:
    field_instruction: Question
    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: 2
eval_max_new_tokens: 128
eval_steps: 500
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: false
group_by_length: true
hub_model_id: abaddon182/9db6cbba-2a7f-4aa3-98b7-fa898ca8f99a
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: 50
lora_alpha: 64
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 5000
micro_batch_size: 2
mlflow_experiment_name: /tmp/757dd5c118de8497_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 10
optim_args:
  adam_beta1: 0.9
  adam_beta2: 0.999
  adam_epsilon: 1e-8
optimizer: adamw_torch_fused
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 500
saves_per_epoch: null
sequence_len: 512
special_tokens:
  pad_token: </s>
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: 98636a02-2a9f-4056-ad93-8df106611163
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 98636a02-2a9f-4056-ad93-8df106611163
warmup_steps: 50
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# 9db6cbba-2a7f-4aa3-98b7-fa898ca8f99a

This model is a fine-tuned version of [echarlaix/tiny-random-mistral](https://huggingface.co/echarlaix/tiny-random-mistral) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 10.2680

## 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_FUSED 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: 5000

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0003 | 1    | 10.3793         |
| 41.1971       | 0.1679 | 500  | 10.2975         |
| 41.1498       | 0.3359 | 1000 | 10.2845         |
| 41.1189       | 0.5038 | 1500 | 10.2774         |
| 41.1108       | 0.6718 | 2000 | 10.2739         |
| 41.0997       | 0.8397 | 2500 | 10.2709         |
| 41.0859       | 1.0076 | 3000 | 10.2694         |
| 41.0844       | 1.1756 | 3500 | 10.2687         |
| 41.0804       | 1.3435 | 4000 | 10.2683         |
| 41.09         | 1.5115 | 4500 | 10.2681         |
| 41.0899       | 1.6794 | 5000 | 10.2680         |


### Framework versions

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