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README.md

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+
+---
+
+library_name: transformers
+base_model: Qwen/Qwen2.5-14B
+tags:
+- axolotl
+- generated_from_trainer
+model-index:
+- name: medius-erebus-magnum-14b
+  results: []
+
+---
+
+[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
+
+
+# QuantFactory/medius-erebus-magnum-14b-GGUF
+This is quantized version of [underwoods/medius-erebus-magnum-14b](https://huggingface.co/underwoods/medius-erebus-magnum-14b) created using llama.cpp
+
+# Original Model Card
+
+
+[<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
+base_model: /workspace/medius-erebus
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+
+hub_model_id: magnum-erebus-14b-v1
+hub_strategy: "all_checkpoints"
+push_dataset_to_hub:
+hf_use_auth_token: true
+
+plugins:
+  - axolotl.integrations.liger.LigerPlugin
+liger_rope: true
+liger_rms_norm: true
+liger_swiglu: true
+liger_fused_linear_cross_entropy: true
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+datasets:
+  - path: anthracite-core/c2_logs_32k_llama3_qwen2_v1.2
+    type: sharegpt
+  - path: anthracite-org/kalo-opus-instruct-22k-no-refusal
+    type: sharegpt
+  - path: lodrick-the-lafted/kalo-opus-instruct-3k-filtered
+    type: sharegpt
+  - path: anthracite-org/nopm_claude_writing_fixed
+    type: sharegpt
+  - path: anthracite-org/kalo_opus_misc_240827
+    type: sharegpt
+  - path: anthracite-org/kalo_misc_part2
+    type: sharegpt
+chat_template: chatml
+shuffle_merged_datasets: true
+default_system_message: "You are an assistant that responds to the user."
+dataset_prepared_path: /workspace/data/magnum-14b-data
+val_set_size: 0.0
+output_dir: /workspace/data/magnum-erebus-14b-fft
+
+sequence_len: 32768
+sample_packing: true
+pad_to_sequence_len: true
+
+adapter:
+lora_model_dir:
+lora_r:
+lora_alpha:
+lora_dropout:
+lora_target_linear:
+lora_fan_in_fan_out:
+
+wandb_project: 14b-magnum-fft
+wandb_entity:
+wandb_watch:
+wandb_name: v4-r2-erebus-attempt-1
+wandb_log_model:
+
+gradient_accumulation_steps: 1
+micro_batch_size: 2
+num_epochs: 2
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.000008
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: false
+
+gradient_checkpointing: unsloth
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+warmup_steps: 40
+evals_per_epoch:
+eval_table_size:
+eval_max_new_tokens:
+saves_per_epoch: 2
+debug:
+deepspeed: deepspeed_configs/zero3_bf16.json
+weight_decay: 0.1
+fsdp:
+fsdp_config:
+special_tokens:
+
+
+```
+
+</details><br>
+
+# medius-erebus-magnum
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 8e-06
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- total_train_batch_size: 16
+- total_eval_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 40
+- num_epochs: 2
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.45.1
+- Pytorch 2.3.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.20.0
+