---
library_name: peft
license: apache-2.0
base_model: NousResearch/Yarn-Solar-10b-64k
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 5d060a25-63b3-4897-a574-bfe425cee4f1
  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-Solar-10b-64k
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - c7e5ee93dd6670d0_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/c7e5ee93dd6670d0_train_data.json
  type:
    field_input: candidates
    field_instruction: clean_html
    field_output: action
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
do_eval: true
early_stopping_patience: 3
eval_batch_size: 4
eval_max_new_tokens: 128
eval_steps: 100
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: true
hub_model_id: lesso16/5d060a25-63b3-4897-a574-bfe425cee4f1
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.000216
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 50
lora_alpha: 128
lora_dropout: 0.15
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: 800
micro_batch_size: 4
mlflow_experiment_name: /tmp/c7e5ee93dd6670d0_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 10
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: 100
saves_per_epoch: null
seed: 160
sequence_len: 1024
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: b8113f60-4278-4105-ba6c-5ae6ade04418
wandb_project: 16a
wandb_run: your_name
wandb_runid: b8113f60-4278-4105-ba6c-5ae6ade04418
warmup_steps: 100
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# 5d060a25-63b3-4897-a574-bfe425cee4f1

This model is a fine-tuned version of [NousResearch/Yarn-Solar-10b-64k](https://huggingface.co/NousResearch/Yarn-Solar-10b-64k) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8362

## 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: 0.000216
- train_batch_size: 4
- eval_batch_size: 4
- seed: 160
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 100
- training_steps: 800

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0006 | 1    | 2.6883          |
| 7.9607        | 0.0585 | 100  | 1.9136          |
| 8.0883        | 0.1170 | 200  | 2.3437          |
| 8.2199        | 0.1755 | 300  | 1.8582          |
| 8.1803        | 0.2340 | 400  | 1.9359          |
| 7.7182        | 0.2925 | 500  | 1.3590          |
| 7.0506        | 0.3510 | 600  | 1.2712          |
| 7.0963        | 0.4095 | 700  | 0.8595          |
| 6.7265        | 0.4680 | 800  | 0.8362          |


### Framework versions

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