---
library_name: peft
license: apache-2.0
base_model: allura-org/Teleut-7b
tags:
- generated_from_trainer
datasets:
- allura-org/neon-41k
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. -->

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<details><summary>See axolotl config</summary>

axolotl version: `0.6.0`
```yaml
base_model: allura-org/Teleut-7b

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_modules:
  - q_proj
  - v_proj
  - k_proj
  - o_proj
lora_target_linear: true
peft_layers_to_transform:
loraplus_lr_ratio: 16

chat_template: chatml
datasets:
  - path: allura-org/neon-41k
    type: chat_template
    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: teleut-7b-rp
mlflow_run_name: v1
hf_mlflow_log_artifacts: true

gradient_accumulation_steps: 1
micro_batch_size: 12
num_epochs: 1
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: 25
debug:
weight_decay: 0.01

```

</details><br>

# ckpts

This model is a fine-tuned version of [allura-org/Teleut-7b](https://huggingface.co/allura-org/Teleut-7b) on the allura-org/neon-41k 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: 12
- eval_batch_size: 12
- seed: 42
- 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: 1

### 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