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---
tags:
- generated_from_trainer
model-index:
- name: magnum-v3-27b-r1
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: `0.4.1`
```yaml
base_model: IntervitensInc_gemma-2-27b-chatml
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
#trust_remote_code: true
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
#- path: anthracite-org/stheno-filtered-v1.1
- path: stheno_data.json
type: sharegpt
conversation: chatml
#- path: anthracite-org/kalo-opus-instruct-22k-no-refusal
- path: kalo_opus_22k.jsonl
type: sharegpt
conversation: chatml
#- path: anthracite-org/nopm_claude_writing_fixed
- path: nopm_claude_dataset.jsonl
type: sharegpt
conversation: chatml
#- path: Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
- path: Epic_Synthstruct.json
type: sharegpt
conversation: chatml
#- path: Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
- path: SynthRP-Gens_processed.json
type: sharegpt
conversation: chatml
chat_template: chatml
shuffle_merged_datasets: true
default_system_message: "You are an assistant that responds to the user."
dataset_prepared_path: magnum-v3-27b-data
val_set_size: 0.0
output_dir: ./magnum-v3-27b-r1
sequence_len: 8192
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len:
adapter:
lora_model_dir:
lora_r:
lora_alpha:
lora_dropout:
lora_target_linear:
lora_fan_in_fan_out:
wandb_project: magnum-v3-27b-r1
wandb_entity:
wandb_watch:
wandb_name: attempt-01
wandb_log_model:
gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 2
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 0.000004
plugins:
- axolotl.integrations.liger.LigerPlugin
liger_cross_entropy: true
#liger_rope: true
#liger_rms_norm: true
#liger_swiglu: true
#liger_fused_linear_cross_entropy: true
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: true
gradient_checkpointing_kwargs:
use_reentrant: false
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
#eager_attention: true
warmup_steps: 40
evals_per_epoch:
eval_table_size:
eval_max_new_tokens:
saves_per_epoch: 2
debug:
deepspeed: /dev/shm/axolotl/deepspeed_configs/zero3_bf16.json
weight_decay: 0.03
fsdp:
# - full_shard
# - auto_wrap
fsdp_config:
# fsdp_limit_all_gathers: true
# fsdp_sync_module_states: true
# fsdp_offload_params: true
# fsdp_use_orig_params: false
# fsdp_cpu_ram_efficient_loading: false
# fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
# fsdp_transformer_layer_cls_to_wrap: LlamaDecoderLayer
# fsdp_state_dict_type: FULL_STATE_DICT
special_tokens:
pad_token: "<pad>"
```
</details><br>
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/intervitens/magnum-v3-27b-r1/runs/6v1sk0zl)
# magnum-v3-27b-r1
This model was trained from scratch on the None 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: 4e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- 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 4.43.2
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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