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sumuks
/
purple-wintermute-0.1-7b

PEFT
Safetensors
axolotl
Generated from Trainer
Model card Files Community
purple-wintermute-0.1-7b
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---
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2.5-7B
tags:
- axolotl
- generated_from_trainer
datasets:
- sumuks/openreview_wintermute_0.1_training_data
model-index:
- name: purple-wintermute-0.1-7b
  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: `0.6.0`
```yaml
base_model: Qwen/Qwen2.5-7B
hub_model_id: sumuks/purple-wintermute-0.1-7b
trust_remote_code: true

load_in_8bit: false
load_in_4bit: false
strict: false
bf16: true
hf_use_auth_token: true

plugins:
  - axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_glu_activation: true
liger_layer_norm: true
liger_fused_linear_cross_entropy: true
save_safetensors:

datasets:
  - path: sumuks/openreview_wintermute_0.1_training_data
    type: completion
    field: text
dataset_prepared_path: .axolotl_cache_data/wintermute_0.1
shuffle_merged_datasets: true
# dataset_exact_deduplication: true
val_set_size: 0.005
output_dir: ./../../outputs/purple-wintermute-0.1-7b
push_dataset_to_hub: sumuks/purple_wintermute_0.1_training_data_in_progress

sequence_length: 2048
sample_packing: true
pad_to_sequence_len: true

adapter: lora
lora_r: 256
lora_alpha: 32
lora_dropout: 0.05
peft_use_rslora: true
lora_target_linear: true

gradient_accumulation_steps: 1
micro_batch_size: 32
eval_batch_size: 1
num_epochs: 3
learning_rate: 5e-5
warmup_ratio: 0.05
evals_per_epoch: 10
saves_per_epoch: 5
gradient_checkpointing: true
lr_scheduler: cosine
optimizer: paged_adamw_8bit

profiler_steps: 100
save_safetensors: true
train_on_inputs: true
wandb_project: wintermute 
wandb_name: purple-wintermute-0.1-7b
deepspeed: deepspeed_configs/zero1.json
```

</details><br>

# purple-wintermute-0.1-7b

This model is a fine-tuned version of [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B) on the sumuks/openreview_wintermute_0.1_training_data dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4027

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 256
- total_eval_batch_size: 8
- optimizer: Use paged_adamw_8bit 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: 386
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.8108        | 0.1002 | 258  | 1.9127          |
| 1.6982        | 0.2004 | 516  | 1.8592          |
| 1.663         | 0.3006 | 774  | 1.8258          |
| 1.585         | 0.4008 | 1032 | 1.7978          |
| 1.5201        | 0.5010 | 1290 | 1.7578          |
| 1.4313        | 0.6012 | 1548 | 1.7181          |
| 1.3256        | 0.7014 | 1806 | 1.6692          |
| 1.2364        | 0.8016 | 2064 | 1.6194          |
| 1.161         | 0.9017 | 2322 | 1.5741          |
| 1.1284        | 1.0016 | 2580 | 1.5281          |
| 1.0433        | 1.1017 | 2838 | 1.4999          |
| 1.0058        | 1.2019 | 3096 | 1.4770          |
| 1.0179        | 1.3021 | 3354 | 1.4603          |
| 0.9993        | 1.4023 | 3612 | 1.4409          |
| 0.99          | 1.5025 | 3870 | 1.4319          |
| 0.9971        | 1.6027 | 4128 | 1.4222          |
| 0.9626        | 1.7029 | 4386 | 1.4126          |
| 0.9396        | 1.8031 | 4644 | 1.4083          |
| 0.9497        | 1.9033 | 4902 | 1.4041          |
| 0.901         | 2.0031 | 5160 | 1.4068          |
| 0.9222        | 2.1033 | 5418 | 1.4081          |
| 0.8882        | 2.2035 | 5676 | 1.4060          |
| 0.9253        | 2.3037 | 5934 | 1.4043          |
| 0.8687        | 2.4039 | 6192 | 1.4035          |
| 0.9058        | 2.5041 | 6450 | 1.4025          |
| 0.8624        | 2.6043 | 6708 | 1.4033          |
| 0.8928        | 2.7045 | 6966 | 1.4028          |
| 0.874         | 2.8047 | 7224 | 1.4029          |
| 0.8892        | 2.9049 | 7482 | 1.4027          |


### Framework versions

- PEFT 0.14.0
- Transformers 4.48.0
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.21.0