---
library_name: peft
license: apache-2.0
base_model: NousResearch/Yarn-Mistral-7b-64k
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 440533d0-4ce2-46c1-8a0e-f65c18162efd
  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-Mistral-7b-64k
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 37c8687d026e9fd5_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/37c8687d026e9fd5_train_data.json
  type:
    field_instruction: question
    field_output: process
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 4
eval_max_new_tokens: 128
eval_steps: 150
eval_table_size: null
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: Romain-XV/440533d0-4ce2-46c1-8a0e-f65c18162efd
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_best_model_at_end: true
load_in_4bit: true
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 128
lora_dropout: 0.3
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 2639
micro_batch_size: 2
mlflow_experiment_name: /tmp/37c8687d026e9fd5_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: 150
sequence_len: 2048
special_tokens:
  pad_token: </s>
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.03300482530545966
wandb_entity: null
wandb_mode: online
wandb_name: a93fe1fb-147c-44b3-88ca-b0335c410502
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: a93fe1fb-147c-44b3-88ca-b0335c410502
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# 440533d0-4ce2-46c1-8a0e-f65c18162efd

This model is a fine-tuned version of [NousResearch/Yarn-Mistral-7b-64k](https://huggingface.co/NousResearch/Yarn-Mistral-7b-64k) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0961

## 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_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: 2639

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.6189        | 0.0001 | 1    | 0.7597          |
| 1.8377        | 0.0082 | 150  | 0.3992          |
| 1.1386        | 0.0164 | 300  | 0.3287          |
| 0.8881        | 0.0246 | 450  | 0.2975          |
| 1.0054        | 0.0328 | 600  | 0.2704          |
| 1.0347        | 0.0410 | 750  | 0.2467          |
| 0.7466        | 0.0491 | 900  | 0.2219          |
| 0.7175        | 0.0573 | 1050 | 0.1994          |
| 0.8256        | 0.0655 | 1200 | 0.1825          |
| 0.731         | 0.0737 | 1350 | 0.1682          |
| 0.5574        | 0.0819 | 1500 | 0.1521          |
| 0.4409        | 0.0901 | 1650 | 0.1386          |
| 0.4958        | 0.0983 | 1800 | 0.1268          |
| 0.4718        | 0.1065 | 1950 | 0.1164          |
| 0.3277        | 0.1147 | 2100 | 0.1075          |
| 0.4109        | 0.1229 | 2250 | 0.1008          |
| 0.3703        | 0.1311 | 2400 | 0.0974          |
| 0.4028        | 0.1393 | 2550 | 0.0961          |


### Framework versions

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