Training in progress, step 16600, checkpoint

checkpoint-16600/README.md

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+---
+library_name: peft
+---
+## Training procedure
+
+
+The following `bitsandbytes` quantization config was used during training:
+- quant_method: bitsandbytes
+- load_in_8bit: False
+- load_in_4bit: True
+- llm_int8_threshold: 6.0
+- llm_int8_skip_modules: None
+- llm_int8_enable_fp32_cpu_offload: False
+- llm_int8_has_fp16_weight: False
+- bnb_4bit_quant_type: nf4
+- bnb_4bit_use_double_quant: True
+- bnb_4bit_compute_dtype: bfloat16
+### Framework versions
+
+
+- PEFT 0.4.0

checkpoint-16600/adapter_config.json

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+{
+  "auto_mapping": null,
+  "base_model_name_or_path": "SkunkworksAI/Mistralic-7B-1",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "lora_alpha": 16.0,
+  "lora_dropout": 0.1,
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 64,
+  "revision": null,
+  "target_modules": [
+    "up_proj",
+    "down_proj",
+    "o_proj",
+    "q_proj",
+    "gate_proj",
+    "v_proj",
+    "k_proj"
+  ],
+  "task_type": "CAUSAL_LM"
+}

checkpoint-16600/adapter_model.bin

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checkpoint-16600/added_tokens.json

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checkpoint-16600/optimizer.pt

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checkpoint-16600/rng_state.pth

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checkpoint-16600/scheduler.pt

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checkpoint-16600/special_tokens_map.json

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checkpoint-16600/tokenizer.model

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checkpoint-16600/tokenizer_config.json

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+  "tokenizer_class": "LlamaTokenizer",
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+  "trust_remote_code": false,
+  "unk_token": "<unk>",
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+  "use_fast": true
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checkpoint-16600/training_args.bin

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