---
library_name: peft
base_model: NousResearch/Yarn-Llama-2-13b-64k
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 2acb31f5-764e-45b9-8e74-92d66daffe15
  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: NousResearch/Yarn-Llama-2-13b-64k
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 113edc9ac50140a9_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/113edc9ac50140a9_train_data.json
  type:
    field_input: context
    field_instruction: question-X
    field_output: answer-Y
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 2
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
hub_model_id: Romain-XV/2acb31f5-764e-45b9-8e74-92d66daffe15
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.00025
load_best_model_at_end: true
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 64
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 840
micro_batch_size: 4
mlflow_experiment_name: /tmp/113edc9ac50140a9_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
s2_attention: null
sample_packing: false
save_steps: 100
sequence_len: 2048
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.04
wandb_entity: null
wandb_mode: online
wandb_name: ff4eacc6-39f5-47c3-942d-394eedd249f4
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: ff4eacc6-39f5-47c3-942d-394eedd249f4
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# 2acb31f5-764e-45b9-8e74-92d66daffe15

This model is a fine-tuned version of [NousResearch/Yarn-Llama-2-13b-64k](https://huggingface.co/NousResearch/Yarn-Llama-2-13b-64k) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4602

## 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: 0.00025
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- 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: 10
- training_steps: 840

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 27.5358       | 0.0010 | 1    | 3.4175          |
| 12.1336       | 0.0996 | 100  | 1.5528          |
| 12.1681       | 0.1992 | 200  | 1.5459          |
| 13.1276       | 0.2988 | 300  | 1.5165          |
| 10.6359       | 0.3984 | 400  | 1.5056          |
| 11.4921       | 0.4979 | 500  | 1.4838          |
| 11.1868       | 0.5975 | 600  | 1.4700          |
| 11.2614       | 0.6971 | 700  | 1.4632          |
| 11.4508       | 0.7967 | 800  | 1.4602          |


### Framework versions

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