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--- |
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license: gpl-3.0 |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: nisten/shqiponja-15b-v1 |
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model-index: |
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- name: shqiponja-15 |
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results: [] |
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datasets: |
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- iamshnoo/alpaca-cleaned-albanian |
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- noxneural/lilium_albanicum_eng_alb |
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--- |
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**15.6b 2expert MoE** |
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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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.0` |
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```yaml |
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base_model: nisten/shqiponja15 |
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model_type: AutoModelForCausalLM |
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tokenizer_type: LlamaTokenizer |
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trust_remote_code: true |
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load_in_8bit: false |
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load_in_4bit: true |
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strict: false |
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datasets: |
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- path: iamshnoo/alpaca-cleaned-albanian |
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type: alpaca |
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shards: 10 |
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- path: noxneural/lilium_albanicum_eng_alb |
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shards: 20 |
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type: |
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field_system: system |
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field_instruction: question |
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field_output: response |
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format: "[INST] {instruction} [/INST]" |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0.0 |
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output_dir: ./alora-out |
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# - model.layers.2[7-9]+.block_sparse_moe.experts.* |
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# - model.layers.3[0-9]+.block_sparse_moe.experts.* |
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# - model.layers.2[7-9]+.b |
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</details><br> |
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``` |
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# alora-out |
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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: 0.0002 |
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- train_batch_size: 10 |
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- eval_batch_size: 10 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 80 |
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- total_eval_batch_size: 40 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 3 |
