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Model: arcee-ai/myalee-v3-L31-8B Source: Original Platform
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README.md
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README.md
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---
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license: llama3.1
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base_model: Crystalcareai/Meta-llama-3.1-8b-instruct
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tags:
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- generated_from_trainer
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model-index:
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- name: outputs/out-myalee
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results: []
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---
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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/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)
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<details><summary>See axolotl config</summary>
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axolotl version: `0.4.1`
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```yaml
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base_model: Crystalcareai/Meta-llama-3.1-8b-instruct
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model_type: AutoTokenizer
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tokenizer_type: AutoTokenizer
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load_in_8bit: false
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load_in_4bit: false
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strict: false
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datasets:
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- path: /workspace/data/myalee
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type: alpaca
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- path: mlabonne/FineTome-100k
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type: sharegpt
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chat_template: llama3
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dataset_prepared_path: last_run_prepared
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# val_set_size: 0.05
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output_dir: ./outputs/out-myalee
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sequence_len: 8192
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sample_packing: true
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pad_to_sequence_len: true
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wandb_project:
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wandb_entity:
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wandb_watch:
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wandb_name:
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wandb_log_model:
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unfrozen_parameters:
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- ^lm_head.weight$
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- ^model.embed_tokens.weight$
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# input_layernorm layers
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- model.layers.0.input_layernorm
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- model.layers.1.input_layernorm
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- model.layers.2.input_layernorm
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- model.layers.3.input_layernorm
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- model.layers.4.input_layernorm
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- model.layers.5.input_layernorm
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- model.layers.6.input_layernorm
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- model.layers.7.input_layernorm
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- model.layers.8.input_layernorm
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- model.layers.9.input_layernorm
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- model.layers.10.input_layernorm
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- model.layers.11.input_layernorm
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- model.layers.12.input_layernorm
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- model.layers.13.input_layernorm
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- model.layers.14.input_layernorm
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- model.layers.15.input_layernorm
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# lm_head layers
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# mlp.down_proj layers
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- model.layers.1.mlp.down_proj
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- model.layers.0.mlp.down_proj
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- model.layers.30.mlp.down_proj
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- model.layers.2.mlp.down_proj
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- model.layers.21.mlp.down_proj
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- model.layers.22.mlp.down_proj
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- model.layers.29.mlp.down_proj
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- model.layers.5.mlp.down_proj
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- model.layers.4.mlp.down_proj
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- model.layers.20.mlp.down_proj
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- model.layers.23.mlp.down_proj
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- model.layers.19.mlp.down_proj
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- model.layers.3.mlp.down_proj
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- model.layers.17.mlp.down_proj
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- model.layers.6.mlp.down_proj
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- model.layers.31.mlp.down_proj
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# mlp.gate_proj layers
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- model.layers.1.mlp.gate_proj
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- model.layers.2.mlp.gate_proj
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- model.layers.3.mlp.gate_proj
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- model.layers.4.mlp.gate_proj
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- model.layers.0.mlp.gate_proj
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- model.layers.25.mlp.gate_proj
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- model.layers.26.mlp.gate_proj
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- model.layers.5.mlp.gate_proj
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- model.layers.24.mlp.gate_proj
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- model.layers.28.mlp.gate_proj
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- model.layers.23.mlp.gate_proj
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- model.layers.27.mlp.gate_proj
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- model.layers.21.mlp.gate_proj
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- model.layers.22.mlp.gate_proj
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- model.layers.29.mlp.gate_proj
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- model.layers.20.mlp.gate_proj
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# mlp.up_proj layers
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- model.layers.4.mlp.up_proj
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- model.layers.3.mlp.up_proj
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- model.layers.0.mlp.up_proj
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- model.layers.5.mlp.up_proj
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- model.layers.7.mlp.up_proj
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- model.layers.6.mlp.up_proj
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- model.layers.2.mlp.up_proj
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- model.layers.1.mlp.up_proj
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- model.layers.8.mlp.up_proj
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- model.layers.12.mlp.up_proj
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- model.layers.14.mlp.up_proj
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- model.layers.9.mlp.up_proj
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- model.layers.15.mlp.up_proj
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- model.layers.17.mlp.up_proj
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- model.layers.13.mlp.up_proj
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- model.layers.19.mlp.up_proj
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# model.embed_tokens layers
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# model.norm layers
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# post_attention_layernorm layers
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- model.layers.0.post_attention_layernorm
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- model.layers.1.post_attention_layernorm
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- model.layers.2.post_attention_layernorm
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- model.layers.3.post_attention_layernorm
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- model.layers.4.post_attention_layernorm
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- model.layers.5.post_attention_layernorm
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- model.layers.6.post_attention_layernorm
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- model.layers.7.post_attention_layernorm
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- model.layers.8.post_attention_layernorm
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- model.layers.9.post_attention_layernorm
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- model.layers.10.post_attention_layernorm
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- model.layers.11.post_attention_layernorm
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- model.layers.12.post_attention_layernorm
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- model.layers.13.post_attention_layernorm
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- model.layers.14.post_attention_layernorm
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- model.layers.15.post_attention_layernorm
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# self_attn.k_proj layers
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- model.layers.29.self_attn.k_proj
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- model.layers.25.self_attn.k_proj
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- model.layers.23.self_attn.k_proj
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- model.layers.28.self_attn.k_proj
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- model.layers.21.self_attn.k_proj
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- model.layers.19.self_attn.k_proj
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- model.layers.22.self_attn.k_proj
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- model.layers.20.self_attn.k_proj
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- model.layers.24.self_attn.k_proj
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- model.layers.31.self_attn.k_proj
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- model.layers.27.self_attn.k_proj
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- model.layers.26.self_attn.k_proj
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- model.layers.17.self_attn.k_proj
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- model.layers.11.self_attn.k_proj
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- model.layers.18.self_attn.k_proj
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- model.layers.14.self_attn.k_proj
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# self_attn.o_proj layers
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- model.layers.14.self_attn.o_proj
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- model.layers.7.self_attn.o_proj
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- model.layers.5.self_attn.o_proj
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- model.layers.11.self_attn.o_proj
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- model.layers.6.self_attn.o_proj
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- model.layers.24.self_attn.o_proj
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- model.layers.9.self_attn.o_proj
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- model.layers.13.self_attn.o_proj
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- model.layers.10.self_attn.o_proj
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- model.layers.12.self_attn.o_proj
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- model.layers.8.self_attn.o_proj
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- model.layers.25.self_attn.o_proj
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- model.layers.21.self_attn.o_proj
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- model.layers.23.self_attn.o_proj
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- model.layers.15.self_attn.o_proj
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- model.layers.16.self_attn.o_proj
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# self_attn.q_proj layers
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- model.layers.8.self_attn.q_proj
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- model.layers.13.self_attn.q_proj
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- model.layers.9.self_attn.q_proj
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- model.layers.14.self_attn.q_proj
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- model.layers.10.self_attn.q_proj
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- model.layers.11.self_attn.q_proj
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- model.layers.0.self_attn.q_proj
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- model.layers.15.self_attn.q_proj
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- model.layers.1.self_attn.q_proj
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- model.layers.6.self_attn.q_proj
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- model.layers.5.self_attn.q_proj
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- model.layers.7.self_attn.q_proj
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- model.layers.12.self_attn.q_proj
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- model.layers.16.self_attn.q_proj
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- model.layers.17.self_attn.q_proj
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- model.layers.26.self_attn.q_proj
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# self_attn.v_proj layers
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- model.layers.26.self_attn.v_proj
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- model.layers.17.self_attn.v_proj
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- model.layers.3.self_attn.v_proj
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- model.layers.28.self_attn.v_proj
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- model.layers.29.self_attn.v_proj
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- model.layers.21.self_attn.v_proj
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- model.layers.15.self_attn.v_proj
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- model.layers.16.self_attn.v_proj
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- model.layers.20.self_attn.v_proj
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- model.layers.25.self_attn.v_proj
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- model.layers.6.self_attn.v_proj
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- model.layers.23.self_attn.v_proj
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- model.layers.4.self_attn.v_proj
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- model.layers.1.self_attn.v_proj
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- model.layers.22.self_attn.v_proj
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- model.layers.14.self_attn.v_proj
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gradient_accumulation_steps: 8
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micro_batch_size: 1
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num_epochs: 4
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optimizer: adamw_torch_fused
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lr_scheduler: cosine
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learning_rate: 2e-5
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train_on_inputs: false
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group_by_length: false
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bf16: auto
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fp16:
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tf32: false
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gradient_checkpointing: true
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gradient_checkpointing_kwargs:
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use_reentrant: false
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early_stopping_patience:
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resume_from_checkpoint:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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warmup_steps: 25
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# evals_per_epoch: 2
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eval_table_size:
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saves_per_epoch: 1
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debug:
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deepspeed:
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weight_decay: 0.0
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fsdp:
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fsdp_config:
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special_tokens:
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pad_token: <|end_of_text|>
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```
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</details><br>
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# outputs/out-myalee
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This model is a fine-tuned version of [Crystalcareai/Meta-llama-3.1-8b-instruct](https://huggingface.co/Crystalcareai/Meta-llama-3.1-8b-instruct) on the None dataset.
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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: 2e-05
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 8
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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: 25
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- num_epochs: 4
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### Training results
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### Framework versions
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- Transformers 4.43.1
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- Pytorch 2.3.1+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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