---
library_name: peft
license: other
base_model: Qwen/Qwen1.5-1.8B
tags:
- axolotl
- generated_from_trainer
model-index:
- name: b82d5463-6b89-4a7b-bbb2-1c4760d1f05b
  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: Qwen/Qwen1.5-1.8B
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - b9b47b46d5c01cab_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/b9b47b46d5c01cab_train_data.json
  type:
    field_input: source
    field_instruction: title
    field_output: comment
    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: 50
eval_table_size: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 16
gradient_checkpointing: true
group_by_length: false
hub_model_id: Romain-XV/b82d5463-6b89-4a7b-bbb2-1c4760d1f05b
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_best_model_at_end: true
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: true
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
lr_scheduler: cosine
max_steps: 518
micro_batch_size: 4
mlflow_experiment_name: /tmp/b9b47b46d5c01cab_train_data.json
model_type: AutoModelForCausalLM
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: 1024
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: e3fe0c30-ee99-44d8-983f-a54143508d00
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: e3fe0c30-ee99-44d8-983f-a54143508d00
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# b82d5463-6b89-4a7b-bbb2-1c4760d1f05b

This model is a fine-tuned version of [Qwen/Qwen1.5-1.8B](https://huggingface.co/Qwen/Qwen1.5-1.8B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.8768

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- 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: 518

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 5.2371        | 0.0017 | 1    | 5.1936          |
| 4.3345        | 0.0837 | 50   | 4.2566          |
| 4.1078        | 0.1675 | 100  | 4.1231          |
| 4.1016        | 0.2512 | 150  | 4.0534          |
| 3.8452        | 0.3349 | 200  | 4.0041          |
| 3.9826        | 0.4186 | 250  | 3.9643          |
| 4.0881        | 0.5024 | 300  | 3.9292          |
| 3.6798        | 0.5861 | 350  | 3.9057          |
| 3.9747        | 0.6698 | 400  | 3.8880          |
| 3.958         | 0.7535 | 450  | 3.8795          |
| 3.8107        | 0.8373 | 500  | 3.8768          |


### Framework versions

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