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--- |
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library_name: peft |
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license: apache-2.0 |
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base_model: allura-org/Teleut-7b |
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tags: |
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- generated_from_trainer |
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datasets: |
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- allura-org/neon-41k |
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model-index: |
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- name: ckpts |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<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) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.6.0` |
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```yaml |
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base_model: allura-org/Teleut-7b |
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load_in_8bit: true |
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load_in_4bit: false |
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plugins: |
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- axolotl.integrations.liger.LigerPlugin |
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liger_rope: true |
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liger_rms_norm: true |
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liger_glu_activation: true |
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liger_fused_linear_cross_entropy: true |
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#unsloth_lora_mlp: true |
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#unsloth_lora_qkv: true |
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#unsloth_lora_o: true |
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strict: false |
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adapter: lora |
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lora_r: 16 |
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lora_alpha: 32 |
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lora_dropout: 0.25 |
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lora_target_modules: |
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- q_proj |
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- v_proj |
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- k_proj |
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- o_proj |
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lora_target_linear: true |
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peft_layers_to_transform: |
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loraplus_lr_ratio: 16 |
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chat_template: chatml |
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datasets: |
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- path: allura-org/neon-41k |
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type: chat_template |
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split: train |
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field_messages: conversations |
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message_field_role: from |
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message_field_content: value |
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dataset_prepared_path: last_run_prepared |
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#val_set_size: 0.02 |
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output_dir: ./ckpts |
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sequence_len: 8192 |
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sample_packing: true |
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pad_to_sequence_len: true |
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#wandb_project: teleut-7b-rp |
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#wandb_entity: |
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#wandb_watch: |
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#wandb_name: |
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#wandb_log_model: checkpoint |
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# mlflow configuration if you're using it |
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mlflow_tracking_uri: https://public-tracking.mlflow-e00zzfjq11ky6jcgtv.backbone-e00bgn6e63256prmhq.msp.eu-north1.nebius.cloud |
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mlflow_experiment_name: teleut-7b-rp |
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mlflow_run_name: v1 |
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hf_mlflow_log_artifacts: true |
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gradient_accumulation_steps: 1 |
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micro_batch_size: 12 |
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num_epochs: 1 |
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optimizer: paged_adamw_8bit |
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lr_scheduler: cosine |
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learning_rate: 6e-5 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: false |
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gradient_checkpointing: unsloth |
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gradient_checkpointing_kwargs: |
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use_reentrant: false |
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early_stopping_patience: |
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resume_from_checkpoint: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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#deepspeed: deepspeed_configs/zero3_bf16.json |
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warmup_steps: 25 |
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#evals_per_epoch: 4 |
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eval_table_size: |
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saves_per_epoch: 25 |
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debug: |
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weight_decay: 0.01 |
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``` |
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</details><br> |
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# ckpts |
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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. |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 6e-05 |
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- train_batch_size: 12 |
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- eval_batch_size: 12 |
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- seed: 42 |
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- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 25 |
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- num_epochs: 1 |
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### Training results |
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### Framework versions |
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- PEFT 0.14.0 |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.1.0 |
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- Tokenizers 0.21.0 |
