CoolFace
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praxisresearch/hf_seed_36b_em_unpop_medcorr_1

sourceHugging Faceupdated 16d agoView on Hugging Face
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Model Card

<!-- 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"/> <details><summary>See axolotl config</summary>

axolotl version: 0.18.0

yaml
adapter: lora

bf16: auto

- message_field_content: content
  message_field_role: role
  path: data/finetuning/correct/health_correct_simplified.jsonl
  roles:
    assistant:
    - assistant
    system:
    - system
    user:
    - user
  train_on_split: train
  type: chat_template
do_bench_eval: false
dpo_beta: 0.1
eval_batch_size: null
eval_sample_packing: false
eval_steps: null
fp16: false
gradient_accumulation_steps: 8
gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: false
group_by_length: false
learning_rate: 1.0e-05
logging_steps: 1
lora_alpha: 64
lora_dropout: 0.0
lora_fan_in_fan_out: false
lora_model_dir: null
lora_r: 32
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
- gate_proj
- up_proj
- down_proj
lr_scheduler: linear
micro_batch_size: 2
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_8bit
output_dir: models/hf_seed_36b_em_unpop_medcorr_1
pad_to_sequence_len: false
peft_use_dora: false
peft_use_rslora: true
push_to_hub: false
save_safetensors: true
saves_per_epoch: 1
sdp_attention: true
seed: 1
sequence_len: 2048
special_tokens: null
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
val_set_size: 0
wandb_entity: tagadearush
wandb_log_model: null
wandb_project: hf_seed_36b_em_unpop_medcorr_1
wandb_run_id: null
wandb_watch: null
warmup_steps: 5
weight_decay: 0.01

</details><br>

models/hfseed36bemunpopmedcorr1

This model was trained from scratch on the data/finetuning/correct/healthcorrectsimplified.jsonl 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: 1e-05
  • —trainbatchsize: 2
  • —evalbatchsize: 2
  • —seed: 1
  • —gradientaccumulationsteps: 8
  • —totaltrainbatch_size: 16
  • —optimizer: Use OptimizerNames.ADAMW8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —lrschedulerwarmup_steps: 5
  • —training_steps: 125

Training results

Framework versions

  • —PEFT 0.19.1
  • —Transformers 5.14.1
  • —Pytorch 2.12.1+cu130
  • —Datasets 4.8.4
  • —Tokenizers 0.22.2