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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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