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---
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2.5-32B-Instruct
tags:
- generated_from_trainer
datasets:
- Fizzarolli/inkmix-v2
language:
- zho
- eng
- fra
- spa
- por
- deu
- ita
- rus
- jpn
- kor
- vie
- tha
- ara
model-index:
- name: ckpts
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/Qwen2.5-32B-Instruct
load_in_8bit: true
load_in_4bit: false
plugins:
- axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_glu_activation: true
liger_fused_linear_cross_entropy: true
#unsloth_lora_mlp: true
#unsloth_lora_qkv: true
#unsloth_lora_o: true
strict: false
adapter: lora
lora_r: 16
lora_alpha: 32
lora_dropout: 0.25
lora_target_linear: true
peft_layers_to_transform:
loraplus_lr_ratio: 16
chat_template: chatml
datasets:
- path: Fizzarolli/inkmix-v2
type: chat_template
chat_template: tokenizer_default
split: train
field_messages: conversations
message_field_role: from
message_field_content: value
dataset_prepared_path: last_run_prepared
#val_set_size: 0.02
output_dir: ./ckpts
sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
#wandb_project: teleut-7b-rp
#wandb_entity:
#wandb_watch:
#wandb_name:
#wandb_log_model: checkpoint
# mlflow configuration if you're using it
mlflow_tracking_uri: https://public-tracking.mlflow-e00zzfjq11ky6jcgtv.backbone-e00bgn6e63256prmhq.msp.eu-north1.nebius.cloud
mlflow_experiment_name: tq-32b-rp-inkmixv2
mlflow_run_name: v1
hf_mlflow_log_artifacts: true
gradient_accumulation_steps: 2
micro_batch_size: 8
num_epochs: 2
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 6e-5
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: unsloth
gradient_checkpointing_kwargs:
use_reentrant: false
early_stopping_patience:
resume_from_checkpoint:
logging_steps: 1
xformers_attention:
flash_attention: true
#deepspeed: deepspeed_configs/zero3_bf16.json
warmup_steps: 25
#evals_per_epoch: 4
eval_table_size:
saves_per_epoch: 10
debug:
weight_decay: 0.05
```
</details><br>
# ckpts
This model is a fine-tuned version of [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct) on the Fizzarolli/inkmix-v2 dataset.
## 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: 6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 25
- num_epochs: 2
### Training results
### Framework versions
- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0 |