End of training

README.md

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+---
+license: other
+base_model: yahma/llama-7b-hf
+tags:
+- generated_from_trainer
+model-index:
+- name: V0224O4
+  results: []
+---
+
+<!-- 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. -->
+
+# V0224O4
+
+This model is a fine-tuned version of [yahma/llama-7b-hf](https://huggingface.co/yahma/llama-7b-hf) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7661
+
+## 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: 0.0003
+- train_batch_size: 4
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 32
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine_with_restarts
+- lr_scheduler_warmup_steps: 20
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 4.1474        | 0.13  | 10   | 1.7099          |
+| 1.306         | 0.26  | 20   | 1.0662          |
+| 0.9881        | 0.39  | 30   | 0.9297          |
+| 0.8907        | 0.52  | 40   | 0.8719          |
+| 0.8543        | 0.65  | 50   | 0.8475          |
+| 0.8285        | 0.78  | 60   | 0.8288          |
+| 0.7987        | 0.91  | 70   | 0.8152          |
+| 0.7878        | 1.04  | 80   | 0.8042          |
+| 0.7603        | 1.17  | 90   | 0.7955          |
+| 0.7743        | 1.3   | 100  | 0.7908          |
+| 0.7619        | 1.43  | 110  | 0.7851          |
+| 0.7517        | 1.55  | 120  | 0.7817          |
+| 0.7411        | 1.68  | 130  | 0.7780          |
+| 0.752         | 1.81  | 140  | 0.7743          |
+| 0.7545        | 1.94  | 150  | 0.7711          |
+| 0.7325        | 2.07  | 160  | 0.7706          |
+| 0.7139        | 2.2   | 170  | 0.7692          |
+| 0.7255        | 2.33  | 180  | 0.7676          |
+| 0.7179        | 2.46  | 190  | 0.7676          |
+| 0.72          | 2.59  | 200  | 0.7670          |
+| 0.7222        | 2.72  | 210  | 0.7665          |
+| 0.7203        | 2.85  | 220  | 0.7660          |
+| 0.721         | 2.98  | 230  | 0.7661          |
+
+
+### Framework versions
+
+- Transformers 4.36.0.dev0
+- Pytorch 2.1.2+cu121
+- Datasets 2.14.6
+- Tokenizers 0.14.1

adapter_config.json

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+{
+  "adaptive_ratio": 1.0,
+  "adaptive_ratio_decay": 1.0,
+  "auto_mapping": null,
+  "base_model_name_or_path": "yahma/llama-7b-hf",
+  "bias": "none",
+  "dynamic_adapter_pool": true,
+  "enable_lora": null,
+  "encoder_hidden_size": 4096,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "input_based_adapter_selection": false,
+  "lora_alpha": 16,
+  "lora_dropout": 0.05,
+  "merge_weights": false,
+  "modules_to_save": null,
+  "num_attention_heads": 32,
+  "num_layers": 32,
+  "num_prefix_set": 8,
+  "num_transformer_submodules": 1,
+  "num_virtual_tokens": 30,
+  "number_of_adapter_pre_layer": 8,
+  "ot_diversified_dispatcher": false,
+  "peft_type": "PREFIX_MA_LORA",
+  "pool_selective_inference": true,
+  "pool_selective_training": true,
+  "prefix_projection": false,
+  "r": 16,
+  "selective_num": 8,
+  "target_modules": [
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "token_dim": 4096
+}

adapter_model.bin

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model.safetensors

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special_tokens_map.json

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tokenizer.model

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tokenizer_config.json

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+  "add_eos_token": false,
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+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": true,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<unk>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}

training_args.bin

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