nisten/shqiponja-15b-v1

15.6b 2expert MoE

<!-- 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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/> <details><summary>See axolotl config</summary>

axolotl version: 0.4.0

base_model: nisten/shqiponja15
model_type: AutoModelForCausalLM
tokenizer_type: LlamaTokenizer
trust_remote_code: true
load_in_8bit: false
load_in_4bit: true
strict: false

datasets:
  - path: iamshnoo/alpaca-cleaned-albanian
    type: alpaca
    shards: 10
  - path: noxneural/lilium_albanicum_eng_alb
    shards: 20
    type:
      field_system: system
      field_instruction: question
      field_output: response
      format: "[INST] {instruction} [/INST]"
dataset_prepared_path: last_run_prepared
val_set_size: 0.0
output_dir: ./alora-out

#  - model.layers.2[7-9]+.block_sparse_moe.experts.*
#  - model.layers.3[0-9]+.block_sparse_moe.experts.*
#  - model.layers.2[7-9]+.b
</details><br>

alora-out

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: 0.0002
• —trainbatchsize: 10
• —evalbatchsize: 10
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 4
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 80
• —totalevalbatch_size: 40
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: cosine
• —lrschedulerwarmup_steps: 10
• —num_epochs: 3