Upload 36 files

cclue_chunk/all_results.json

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+{
+    "epoch": 3.0,
+    "train_loss": 0.16342519847783207,
+    "train_runtime": 12079.5406,
+    "train_samples_per_second": 0.863,
+    "train_steps_per_second": 0.043
+}

cclue_chunk/cclue_chunk.json

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+{
+    "desc": "CCLUE-MRC数据集,使用随机选择的关键句训练",
+    "output_dir": "output/ablation_study/CCLUE/cclue_chunk",
+    "model_name_or_path": "/data0/maqi/huggingface_models/option1-models/option1-ncr_ft",
+    "train_file": "/data0/maqi/KGLQA-data/datasets/CCLUE/random_select/cclue_chunk_1400_instruct/train.jsonl",
+    "num_train_epochs": 3,
+    "per_device_train_batch_size": 10,
+    "gradient_accumulation_steps": 2,
+    "learning_rate": 1e-4,
+    "max_seq_length": 1400,
+    "logging_steps": 20,
+    "save_steps": 300,
+    "save_total_limit": 1,
+    "lr_scheduler_type": "constant_with_warmup",
+    "warmup_ratio": 0.1,
+    "lora_rank": 128,
+    "lora_alpha": 64,
+    "lora_dropout": 0.05,
+
+    "gradient_checkpointing": true,
+    "disable_tqdm": false,
+    "optim": "paged_adamw_32bit",
+    "seed": 318,
+    "fp16": true,
+    "report_to": "tensorboard",
+    "dataloader_num_workers": 10,
+    "save_strategy": "steps",
+    "weight_decay": 0,
+    "max_grad_norm": 0.3,
+    "remove_unused_columns": false
+}

cclue_chunk/final/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: float16
+### Framework versions
+
+
+- PEFT 0.5.0

cclue_chunk/final/adapter_config.json

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+{
+  "auto_mapping": null,
+  "base_model_name_or_path": "/data0/maqi/huggingface_models/option1-models/option1-ncr_ft",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "lora_alpha": 64,
+  "lora_dropout": 0.05,
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 128,
+  "revision": null,
+  "target_modules": [
+    "o_proj",
+    "q_proj",
+    "k_proj",
+    "gate_proj",
+    "v_proj",
+    "up_proj",
+    "down_proj"
+  ],
+  "task_type": "CAUSAL_LM"
+}

cclue_chunk/final/adapter_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a0c823fb71e42cead01b86b9e88509765b5fe536ad6287aab86c0740931a38b7
+size 1279424269

cclue_chunk/final/training_args.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:547374acdce650b0f971a2c2e34dfe9400514b410fede6e41531ee3b787f6020
+size 4091

cclue_chunk/train.log

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+model training desc:  CCLUE-MRC数据集,使用随机选择的关键句训练
+2023-12-06 10:40:28.159 | INFO     | __main__:init_components:108 - Initializing components...
+
+You are using the default legacy behaviour of the <class 'transformers.models.llama.tokenization_llama.LlamaTokenizer'>. If you see this, DO NOT PANIC! This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thouroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
+2023-12-06 10:41:21.733 | INFO     | __main__:init_components:155 - 
+
+2023-12-06 10:41:21.733 | INFO     | __main__:init_components:156 - ********************
+2023-12-06 10:41:21.733 | INFO     | __main__:init_components:157 - using llama2 model
+2023-12-06 10:41:21.733 | INFO     | __main__:init_components:158 - ********************
+2023-12-06 10:41:21.733 | INFO     | __main__:init_components:159 - 
+
+memory footprint of model: 5.472740173339844 GB
+trainable params: 319,815,680 || all params: 7,447,007,232 || trainable%: 4.294553100818044
+2023-12-06 10:42:04.751 | INFO     | component.dataset:__init__:14 - Loading data: /data0/maqi/KGLQA-data/datasets/CCLUE/random_select/cclue_chunk_1400_instruct/train.jsonl
+2023-12-06 10:42:04.804 | INFO     | component.dataset:__init__:19 - there are 3473 data in dataset
+2023-12-06 10:42:04.946 | INFO     | __main__:main:231 - *** starting training ***
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+
                                                   
+
+***** train metrics *****
+  epoch                    =        3.0
+  train_loss               =     0.1634
+  train_runtime            = 3:21:19.54
+  train_samples_per_second =      0.863
+  train_steps_per_second   =      0.043

cclue_chunk/train_results.json

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cclue_random_select/all_results.json

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+{
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cclue_random_select/cclue_random_select.json

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+{
+    "desc": "CCLUE-MRC数据集,使用随机选择的关键句训练",
+    "output_dir": "output/ablation_study/NCR/cclue_random_select",
+    "model_name_or_path": "/data0/maqi/huggingface_models/option1-models/option1-ncr_ft",
+    "train_file": "/data0/maqi/KGLQA-data/datasets/CCLUE/random_select/cclue_random_1400_instruct/train.jsonl",
+    "num_train_epochs": 3,
+    "per_device_train_batch_size": 10,
+    "gradient_accumulation_steps": 2,
+    "learning_rate": 1e-4,
+    "max_seq_length": 1400,
+    "logging_steps": 20,
+    "save_steps": 300,
+    "save_total_limit": 1,
+    "lr_scheduler_type": "constant_with_warmup",
+    "warmup_ratio": 0.1,
+    "lora_rank": 128,
+    "lora_alpha": 64,
+    "lora_dropout": 0.05,
+
+    "gradient_checkpointing": true,
+    "disable_tqdm": false,
+    "optim": "paged_adamw_32bit",
+    "seed": 318,
+    "fp16": true,
+    "report_to": "tensorboard",
+    "dataloader_num_workers": 10,
+    "save_strategy": "steps",
+    "weight_decay": 0,
+    "max_grad_norm": 0.3,
+    "remove_unused_columns": false
+}

cclue_random_select/final/README.md

@@ -0,0 +1,21 @@
+---
+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: float16
+### Framework versions
+
+
+- PEFT 0.5.0

cclue_random_select/final/adapter_config.json

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+{
+  "auto_mapping": null,
+  "base_model_name_or_path": "/data0/maqi/huggingface_models/option1-models/option1-ncr_ft",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "lora_alpha": 64,
+  "lora_dropout": 0.05,
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 128,
+  "revision": null,
+  "target_modules": [
+    "o_proj",
+    "up_proj",
+    "k_proj",
+    "v_proj",
+    "down_proj",
+    "gate_proj",
+    "q_proj"
+  ],
+  "task_type": "CAUSAL_LM"
+}

cclue_random_select/final/adapter_model.bin

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+oid sha256:7a4d523922cc3cf3af372f2f873b9af5a9df351ac058ab39932972dc8895499a
+size 1279424269

cclue_random_select/final/training_args.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:87041b9b5103f4e4444137da6d7f6839ccb09c2a025db7a79a30e10edad0a577
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cclue_random_select/train.log

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+model training desc:  CCLUE-MRC数据集,使用随机选择的关键句训练
+2023-12-04 18:36:01.480 | INFO     | __main__:init_components:108 - Initializing components...
+
+You are using the default legacy behaviour of the <class 'transformers.models.llama.tokenization_llama.LlamaTokenizer'>. If you see this, DO NOT PANIC! This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thouroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
+2023-12-04 18:36:26.640 | INFO     | __main__:init_components:155 - 
+
+2023-12-04 18:36:26.640 | INFO     | __main__:init_components:156 - ********************
+2023-12-04 18:36:26.640 | INFO     | __main__:init_components:157 - using llama2 model
+2023-12-04 18:36:26.640 | INFO     | __main__:init_components:158 - ********************
+2023-12-04 18:36:26.640 | INFO     | __main__:init_components:159 - 
+
+memory footprint of model: 5.472740173339844 GB
+trainable params: 319,815,680 || all params: 7,447,007,232 || trainable%: 4.294553100818044
+2023-12-04 18:37:07.959 | INFO     | component.dataset:__init__:14 - Loading data: /data0/maqi/KGLQA-data/datasets/CCLUE/random_select/cclue_random_1400_instruct/train.jsonl
+2023-12-04 18:37:07.983 | INFO     | component.dataset:__init__:19 - there are 3473 data in dataset
+2023-12-04 18:37:08.021 | INFO     | __main__:main:231 - *** starting training ***
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+
                                                   
+
+***** train metrics *****
+  epoch                    =        3.0
+  train_loss               =     0.1626
+  train_runtime            = 3:22:24.15
+  train_samples_per_second =      0.858
+  train_steps_per_second   =      0.043

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ncr_chunk/all_results.json

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ncr_chunk/final/README.md

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+---
+library_name: peft
+base_model: /data0/maqi/huggingface_models/TechGPT-7B
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure 
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+
+
+## 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: float16
+
+### Framework versions
+
+
+- PEFT 0.6.2

ncr_chunk/final/adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/data0/maqi/huggingface_models/TechGPT-7B",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "lora_alpha": 64,
+  "lora_dropout": 0.05,
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 128,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "down_proj",
+    "k_proj",
+    "gate_proj",
+    "o_proj",
+    "q_proj",
+    "v_proj",
+    "up_proj"
+  ],
+  "task_type": "CAUSAL_LM"
+}

ncr_chunk/final/adapter_model.bin

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ncr_chunk/ncr_chunk.json

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+{
+    "desc": "使用随机选择的关键句训练",
+    "output_dir": "output/ablation_study/NCR/ncr_chunk",
+    "model_name_or_path": "/data0/maqi/huggingface_models/TechGPT-7B",
+    "train_file": "/data0/maqi/KGLQA-data/datasets/NCR/random_select/ncr_chunk_1400_instruct/train.jsonl",
+    "num_train_epochs": 3,
+    "per_device_train_batch_size": 10,
+    "gradient_accumulation_steps": 2,
+    "learning_rate": 1e-4,
+    "max_seq_length": 1400,
+    "logging_steps": 20,
+    "save_steps": 300,
+    "save_total_limit": 5,
+    "lr_scheduler_type": "constant_with_warmup",
+    "warmup_ratio": 0.1,
+    "lora_rank": 128,
+    "lora_alpha": 64,
+    "lora_dropout": 0.05,
+
+    "gradient_checkpointing": true,
+    "disable_tqdm": false,
+    "optim": "paged_adamw_32bit",
+    "seed": 318,
+    "fp16": true,
+    "report_to": "tensorboard",
+    "dataloader_num_workers": 10,
+    "save_strategy": "steps",
+    "weight_decay": 0,
+    "max_grad_norm": 0.3,
+    "remove_unused_columns": false
+}

ncr_chunk/train.log

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+WARNING:torch.distributed.run:
+*****************************************
+Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
+*****************************************
+model training desc:  使用随机选择的关键句训练
+2023-12-06 10:34:27.251 | INFO     | __main__:init_components:108 - Initializing components...
+model training desc:  使用随机选择的关键句训练
+2023-12-06 10:34:27.257 | INFO     | __main__:init_components:108 - Initializing components...
+You are using the default legacy behaviour of the <class 'transformers.models.llama.tokenization_llama.LlamaTokenizer'>. If you see this, DO NOT PANIC! This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thouroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
+2023-12-06 10:34:47.365 | INFO     | __main__:init_components:143 - 
+
+2023-12-06 10:34:47.365 | INFO     | __main__:init_components:144 - ********************
+2023-12-06 10:34:47.365 | INFO     | __main__:init_components:145 - using TechGPT-7B
+2023-12-06 10:34:47.365 | INFO     | __main__:init_components:146 - ********************
+2023-12-06 10:34:47.365 | INFO     | __main__:init_components:147 - 
+
+memory footprint of model: 5.472740173339844 GB
+You are using the default legacy behaviour of the <class 'transformers.models.llama.tokenization_llama.LlamaTokenizer'>. If you see this, DO NOT PANIC! This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thouroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
+2023-12-06 10:34:48.089 | INFO     | __main__:init_components:143 - 
+
+2023-12-06 10:34:48.090 | INFO     | __main__:init_components:144 - ********************
+2023-12-06 10:34:48.090 | INFO     | __main__:init_components:145 - using TechGPT-7B
+2023-12-06 10:34:48.090 | INFO     | __main__:init_components:146 - ********************
+2023-12-06 10:34:48.090 | INFO     | __main__:init_components:147 - 
+
+memory footprint of model: 5.472740173339844 GB
+trainable params: 319,815,680 || all params: 7,447,007,232 || trainable%: 4.294553100818044
+2023-12-06 10:34:50.010 | INFO     | component.dataset:__init__:14 - Loading data: /data0/maqi/KGLQA-data/datasets/NCR/random_select/ncr_chunk_1400_instruct/train.jsonl
+2023-12-06 10:34:50.112 | INFO     | component.dataset:__init__:19 - there are 15319 data in dataset
+2023-12-06 10:34:50.170 | INFO     | __main__:main:231 - *** starting training ***
+trainable params: 319,815,680 || all params: 7,447,007,232 || trainable%: 4.294553100818044
+2023-12-06 10:34:50.758 | INFO     | component.dataset:__init__:14 - Loading data: /data0/maqi/KGLQA-data/datasets/NCR/random_select/ncr_chunk_1400_instruct/train.jsonl
+2023-12-06 10:34:50.857 | INFO     | component.dataset:__init__:19 - there are 15319 data in dataset
+2023-12-06 10:34:50.875 | INFO     | __main__:main:231 - *** starting training ***
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+
+***** train metrics *****
+  epoch                    =         3.0
+  train_loss               =      0.6199
+  train_runtime            = 10:27:20.64
+  train_samples_per_second =       1.221
+  train_steps_per_second   =       0.031

ncr_chunk/train_results.json

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ncr_chunk/trainer_state.json

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ncr_random_select/all_results.json

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+{
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ncr_random_select/final/README.md

@@ -0,0 +1,220 @@
+---
+library_name: peft
+base_model: /data0/maqi/huggingface_models/TechGPT-7B
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure 
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+
+
+## 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: float16
+
+### Framework versions
+
+
+- PEFT 0.6.2

ncr_random_select/final/adapter_config.json

@@ -0,0 +1,28 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "/data0/maqi/huggingface_models/TechGPT-7B",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "lora_alpha": 64,
+  "lora_dropout": 0.05,
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 128,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "k_proj",
+    "up_proj",
+    "v_proj",
+    "o_proj",
+    "q_proj",
+    "down_proj",
+    "gate_proj"
+  ],
+  "task_type": "CAUSAL_LM"
+}

ncr_random_select/final/adapter_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:42c178ff60721fd905bd7f2dfd5b457f0a9660777c794354bc0b396d484d14fe
+size 1279424269

ncr_random_select/final/training_args.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ba7085c40a67a0c30faf03a01d0468e920daf08ef5e1cc92472893b86a508552
+size 4091

ncr_random_select/ncr_random_select.json

@@ -0,0 +1,31 @@
+{
+    "desc": "使用随机选择的关键句训练",
+    "output_dir": "output/ablation_study/NCR/ncr_random_select",
+    "model_name_or_path": "/data0/maqi/huggingface_models/TechGPT-7B",
+    "train_file": "/data0/maqi/KGLQA-data/datasets/NCR/random_select/ncr_random_1400_instruct/train.jsonl",
+    "num_train_epochs": 3,
+    "per_device_train_batch_size": 10,
+    "gradient_accumulation_steps": 2,
+    "learning_rate": 1e-4,
+    "max_seq_length": 1400,
+    "logging_steps": 20,
+    "save_steps": 300,
+    "save_total_limit": 1,
+    "lr_scheduler_type": "constant_with_warmup",
+    "warmup_ratio": 0.1,
+    "lora_rank": 128,
+    "lora_alpha": 64,
+    "lora_dropout": 0.05,
+
+    "gradient_checkpointing": true,
+    "disable_tqdm": false,
+    "optim": "paged_adamw_32bit",
+    "seed": 318,
+    "fp16": true,
+    "report_to": "tensorboard",
+    "dataloader_num_workers": 10,
+    "save_strategy": "steps",
+    "weight_decay": 0,
+    "max_grad_norm": 0.3,
+    "remove_unused_columns": false
+}

ncr_random_select/train.log

@@ -0,0 +1,99 @@
+WARNING:torch.distributed.run:
+*****************************************
+Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed. 
+*****************************************
+model training desc:  使用随机选择的关键句训练
+2023-12-07 13:36:09.354 | INFO     | __main__:init_components:108 - Initializing components...
+model training desc:  使用随机选择的关键句训练
+2023-12-07 13:36:09.360 | INFO     | __main__:init_components:108 - Initializing components...
+You are using the default legacy behaviour of the <class 'transformers.models.llama.tokenization_llama.LlamaTokenizer'>. If you see this, DO NOT PANIC! This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thouroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
+2023-12-07 13:36:37.046 | INFO     | __main__:init_components:143 - 
+
+2023-12-07 13:36:37.046 | INFO     | __main__:init_components:144 - ********************
+2023-12-07 13:36:37.046 | INFO     | __main__:init_components:145 - using TechGPT-7B
+2023-12-07 13:36:37.046 | INFO     | __main__:init_components:146 - ********************
+2023-12-07 13:36:37.046 | INFO     | __main__:init_components:147 - 
+
+memory footprint of model: 5.472740173339844 GB
+You are using the default legacy behaviour of the <class 'transformers.models.llama.tokenization_llama.LlamaTokenizer'>. If you see this, DO NOT PANIC! This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thouroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
+2023-12-07 13:36:37.818 | INFO     | __main__:init_components:143 - 
+
+2023-12-07 13:36:37.819 | INFO     | __main__:init_components:144 - ********************
+2023-12-07 13:36:37.819 | INFO     | __main__:init_components:145 - using TechGPT-7B
+2023-12-07 13:36:37.819 | INFO     | __main__:init_components:146 - ********************
+2023-12-07 13:36:37.819 | INFO     | __main__:init_components:147 - 
+
+memory footprint of model: 5.472740173339844 GB
+trainable params: 319,815,680 || all params: 7,447,007,232 || trainable%: 4.294553100818044
+2023-12-07 13:36:39.748 | INFO     | component.dataset:__init__:14 - Loading data: /data0/maqi/KGLQA-data/datasets/NCR/random_select/ncr_random_1400_instruct/train.jsonl
+2023-12-07 13:36:39.846 | INFO     | component.dataset:__init__:19 - there are 15319 data in dataset
+2023-12-07 13:36:39.938 | INFO     | __main__:main:231 - *** starting training ***
+trainable params: 319,815,680 || all params: 7,447,007,232 || trainable%: 4.294553100818044
+2023-12-07 13:36:40.517 | INFO     | component.dataset:__init__:14 - Loading data: /data0/maqi/KGLQA-data/datasets/NCR/random_select/ncr_random_1400_instruct/train.jsonl
+2023-12-07 13:36:40.618 | INFO     | component.dataset:__init__:19 - there are 15319 data in dataset
+2023-12-07 13:36:40.712 | INFO     | __main__:main:231 - *** starting training ***
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+
+***** train metrics *****
+  epoch                    =         3.0
+  train_loss               =      0.6322
+  train_runtime            = 10:30:40.36
+  train_samples_per_second =       1.214
+  train_steps_per_second   =        0.03

ncr_random_select/train_results.json

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+{
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+    "train_steps_per_second": 0.03
+}

ncr_random_select/trainer_state.json

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