---
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2.5-7B
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 1433c5b3-ebeb-46e5-ba6e-3d887858c7ae
  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/Qwen2.5-7B
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - df3e193d2d64633a_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/df3e193d2d64633a_train_data.json
  type:
    field_instruction: input_field
    field_output: output_field
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: false
fp16: true
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: Nexspear/1433c5b3-ebeb-46e5-ba6e-3d887858c7ae
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0001
load_in_4bit: false
load_in_8bit: false
local_rank: 0
logging_steps: 3
lora_alpha: 128
lora_dropout: 0.1
lora_fan_in_fan_out: true
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
max_memory:
  0: 72GB
max_steps: 50
micro_batch_size: 8
mlflow_experiment_name: /tmp/df3e193d2d64633a_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: false
sample_packing: false
saves_per_epoch: 4
sequence_len: 1024
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: leixa-personal
wandb_mode: online
wandb_name: 1433c5b3-ebeb-46e5-ba6e-3d887858c7ae
wandb_project: Gradients-On-Four
wandb_run: your_name
wandb_runid: 1433c5b3-ebeb-46e5-ba6e-3d887858c7ae
warmup_steps: 10
weight_decay: 0.01
xformers_attention: null

```

</details><br>

# 1433c5b3-ebeb-46e5-ba6e-3d887858c7ae

This model is a fine-tuned version of [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1301

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 0.1   | 1    | 1.4759          |
| 1.4056        | 0.3   | 3    | 1.4382          |
| 1.3039        | 0.6   | 6    | 1.2148          |
| 1.1307        | 0.9   | 9    | 1.1424          |
| 1.0364        | 1.2   | 12   | 1.1045          |
| 0.8639        | 1.5   | 15   | 1.0964          |
| 0.8137        | 1.8   | 18   | 1.1080          |
| 0.7955        | 2.1   | 21   | 1.1107          |
| 0.6105        | 2.4   | 24   | 1.1176          |
| 0.5713        | 2.7   | 27   | 1.1273          |
| 0.5685        | 3.0   | 30   | 1.1301          |


### Framework versions

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