Narkantak/mistral-7b-Labelled-SLM

README.md

@@ -16,7 +16,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GPTQ) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4531
+- eval_loss: 1.0970
+- eval_runtime: 1.8296
+- eval_samples_per_second: 1.093
+- eval_steps_per_second: 0.547
+- epoch: 12.0
+- step: 16
 
 ## Model description
 
@@ -36,68 +41,17 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.0002
-- train_batch_size: 6
-- eval_batch_size: 6
+- train_batch_size: 5
+- eval_batch_size: 5
 - seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 24
+- gradient_accumulation_steps: 3
+- total_train_batch_size: 15
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 2
+- lr_scheduler_warmup_steps: 1
 - num_epochs: 50
 - mixed_precision_training: Native AMP
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss |
-|:-------------:|:-----:|:----:|:---------------:|
-| 5.1986        | 0.89  | 6    | 3.6826          |
-| 2.8565        | 1.93  | 13   | 2.2686          |
-| 1.6562        | 2.96  | 20   | 1.1494          |
-| 0.919         | 4.0   | 27   | 0.8274          |
-| 0.8226        | 4.89  | 33   | 0.7219          |
-| 0.6004        | 5.93  | 40   | 0.6329          |
-| 0.5166        | 6.96  | 47   | 0.5777          |
-| 0.4662        | 8.0   | 54   | 0.5476          |
-| 0.497         | 8.89  | 60   | 0.5241          |
-| 0.3909        | 9.93  | 67   | 0.5034          |
-| 0.3628        | 10.96 | 74   | 0.4779          |
-| 0.3381        | 12.0  | 81   | 0.4718          |
-| 0.3768        | 12.89 | 87   | 0.4562          |
-| 0.3121        | 13.93 | 94   | 0.4557          |
-| 0.3022        | 14.96 | 101  | 0.4528          |
-| 0.2995        | 16.0  | 108  | 0.4449          |
-| 0.3423        | 16.89 | 114  | 0.4521          |
-| 0.2929        | 17.93 | 121  | 0.4319          |
-| 0.2899        | 18.96 | 128  | 0.4354          |
-| 0.2873        | 20.0  | 135  | 0.4402          |
-| 0.3325        | 20.89 | 141  | 0.4465          |
-| 0.2828        | 21.93 | 148  | 0.4420          |
-| 0.2813        | 22.96 | 155  | 0.4426          |
-| 0.2817        | 24.0  | 162  | 0.4408          |
-| 0.3255        | 24.89 | 168  | 0.4417          |
-| 0.2793        | 25.93 | 175  | 0.4404          |
-| 0.2772        | 26.96 | 182  | 0.4385          |
-| 0.279         | 28.0  | 189  | 0.4409          |
-| 0.3247        | 28.89 | 195  | 0.4429          |
-| 0.2775        | 29.93 | 202  | 0.4421          |
-| 0.2769        | 30.96 | 209  | 0.4409          |
-| 0.2779        | 32.0  | 216  | 0.4423          |
-| 0.322         | 32.89 | 222  | 0.4450          |
-| 0.2767        | 33.93 | 229  | 0.4484          |
-| 0.2771        | 34.96 | 236  | 0.4455          |
-| 0.2761        | 36.0  | 243  | 0.4476          |
-| 0.3212        | 36.89 | 249  | 0.4485          |
-| 0.2751        | 37.93 | 256  | 0.4503          |
-| 0.2766        | 38.96 | 263  | 0.4522          |
-| 0.2768        | 40.0  | 270  | 0.4488          |
-| 0.321         | 40.89 | 276  | 0.4498          |
-| 0.2743        | 41.93 | 283  | 0.4518          |
-| 0.2746        | 42.96 | 290  | 0.4527          |
-| 0.2751        | 44.0  | 297  | 0.4532          |
-| 0.2867        | 44.44 | 300  | 0.4531          |
-
-
 ### Framework versions
 
 - PEFT 0.10.0

adapter_config.json

@@ -1,7 +1,7 @@
 {
   "alpha_pattern": {},
   "auto_mapping": null,
-  "base_model_name_or_path": null,
+  "base_model_name_or_path": "TheBloke/Mistral-7B-Instruct-v0.2-GPTQ",
   "bias": "none",
   "fan_in_fan_out": false,
   "inference_mode": true,

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test.csv

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+example
+"[INST] Orion, Act as a financial analyst with a photographic memory and respond to the user query based on the type of document type. \  
+Orion is known for its best precision and world class accuracy with the financial knowledge, \  
+Document Type: Document Type 7
+
+, context associated to the document type is 
+
+No Information Available [/INST] "
+"[INST] Orion, Act as a financial analyst with a photographic memory and respond to the user query based on the type of document type. \  
+Orion is known for its best precision and world class accuracy with the financial knowledge, \  
+Document Type: Document Type 1
+
+, context associated to the document type is 
+
+(DT - OMB control number: 1545-0047/Expiration Date: 12/31/2019)(DOL - OMB control number: 1210-0147/Expiration date: 5/31/2022) Page 1 of 5
+(HHS - OMB control number: 0938-1146/Expiration date: 10/31/2022)
+Summary of Benefits and Coverage: What this Plan Covers & What You Pay for Covered Services Coverage Period: Beginning on or after 01/01/2021
+Community Blue – Faculty/Acad Active: Michigan State University Coverage for: Individual/Family | PlanType:PPO
+The Summary of Benefits and Coverage (SBC) document will help you choose a health plan. The SBC shows you how you and the plan would share the cost for covered health care services. NOTE: Information about the cost of this plan (called the premium) will be provided separately. This is only a summary. For more information about your coverage, or to get a copy of the complete terms of coverage, visit www.bcbsm.com or call 888-288-1726. For general definitions of common terms, such as allowed amount, balance billing, coinsurance, copayment, deductible, provider, or other underlined terms, see the Glossary. You can view the Glossary at https://www.healthcare.gov/sbc-glossary or call 888-288-1726 to request a copy.
+Important Questions Answers Why This Matters: In-Network Out-of-Network
+What is the overall deductible?
+$100 Individual/ $200 Family
+$250 Individual/
+$500 Family
+Generally, you must pay all of the costs from provider's up to the deductible amount before this plan begins to pay. If you have other family members on the plan, each family member must meet their own individual deductible until the total amount of deductible expenses paid by all family members meets the overall family deductible. Are there services covered before you meet your deductible? Yes This plan covers some items and services even if you haven’t yet met the deductible amount. But a copayment or coinsurance may apply. For example, this plan covers certain preventive services without cost-sharing and before you meet your deductible. See a list of covered preventive services at https://www.healthcare.gov/coverage/preventive-care-benefits/
+Are there other deductibles for specific services?
+No
+You don’t have to meet deductibles for specific services. What is the out-of-pocket limit for this plan? $2,000 Individual/ $4,000 Family $2,000 Individual/ $4,000 Family Plus deductible The out-of-pocket limit is the most you could pay in a year for covered services. If you have other family members in this plan, they have to meet their own out-of-pocket limits until the overall family out-of-pocket limit has been met.
+What is not included in the out-of-pocket limit?
+Premiums, balance-billed charges, any pharmacy penalty and health care this plan doesn’t cover.
+Even though you pay these expenses, they don’t count toward the out-of-pocket limit. Will you pay less if you use a network provider? Yes. For a list of in-network providers, see www.bcbsm.com or call the number on the back of your BCBSM ID card. This plan uses a provider network. You will pay less if you use a provider in the plan’s network. You will pay the most if you use an out-of-network provider, and you might receive a bill from a provider for the difference between the provider’s charge and what your plan pays (balance billing).
+Do you need a referral to see a specialist?
+No
+You can see the specialist you choose without a referral. [/INST] "

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train.csv

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+example
+"[INST] Orion, Act as a financial analyst with a photographic memory and respond to the user query based on the type of document type. \  
+Orion is known for its best precision and world class accuracy with the financial knowledge, \  
+Document Type: Document Type 8
+
+, context associated to the document type is 
+
+EcoGuardians is a visionary environmental organization dedicated to safeguarding our planet for future generations. Committed to promoting sustainability, conservation, and environmental awareness, EcoGuardians strives to protect biodiversity, combat climate change, and advocate for eco-friendly practices.
+Through innovative projects, educational initiatives, and community engagement, EcoGuardians empowers individuals to make a positive impact on the environment. By fostering a culture of environmental stewardship, EcoGuardians aims to inspire collective action towards a greener, more sustainable world. [/INST] "
+"[INST] Orion, Act as a financial analyst with a photographic memory and respond to the user query based on the type of document type. \  
+Orion is known for its best precision and world class accuracy with the financial knowledge, \  
+Document Type: Document Type 9
+
+, context associated to the document type is 
+
+No Information Available [/INST] "
+"[INST] Orion, Act as a financial analyst with a photographic memory and respond to the user query based on the type of document type. \  
+Orion is known for its best precision and world class accuracy with the financial knowledge, \  
+Document Type: Document Type 6
+
+, context associated to the document type is 
+
+No Information Available [/INST] "
+"[INST] Orion, Act as a financial analyst with a photographic memory and respond to the user query based on the type of document type. \  
+Orion is known for its best precision and world class accuracy with the financial knowledge, \  
+Document Type: Document Type 5
+
+, context associated to the document type is 
+
+1 of 5
+Summary of Benefits and Coverage: What this Plan Covers & What You Pay For Covered Services Coverage Period: 01/01/2018 – 12/31/2018
+Insurance Company 1: Plan Option 1 Coverage for: Family | Plan Type: PPO
+The Summary of Benefits and Coverage (SBC) document will help you choose a health plan. The SBC shows you how you and the plan would share the cost for covered health care services. NOTE: Information about the cost of this plan (called the premium) will be provided separately. This is only a summary. For more information about your coverage, or to get a copy of the complete terms of coverage, [insert contact information]. For general definitions of common terms, such as allowed amount, balance billing, coinsurance, copayment, deductible, provider, or other underlined terms see the Glossary. You can view the Glossary at www.[insert].com or call 1-800-[insert] to request a copy.
+Important Questions Answers Why This Matters:
+What is the overall deductible?
+$500/Individual or $1,000/family
+Generally, you must pay all of the costs from providers up to the deductible amount before this plan begins to pay. If you have other family members on the plan, each family member must meet their own individual deductible until the total amount of deductible expenses paid by all family members meets the overall family deductible. Are there services covered before you meet your deductible? Yes. Preventive care and primary care services are covered before you meet your deductible. This plan covers some items and services even if you haven’t yet met the deductible amount. But a copayment or coinsurance may apply. For example, this plan covers certain preventive services without cost-sharing and before you meet your deductible. See a list of covered preventive services at https://www.healthcare.gov/coverage/preventive-care-benefits/. Are there other deductibles for specific services? Yes. $300 for prescription drug coverage and $300 for occupational therapy services. You must pay all of the costs for these services up to the specific deductible amount before this plan begins to pay for these services. What is the out-of-pocket limit for this plan? For network providers $2,500 individual / $5,000 family; for out-of-network providers $4,000 individual / $8,000 family The out-of-pocket limit is the most you could pay in a year for covered services. If you have other family members in this plan, they have to meet their own out-of-pocket limits until the overall family out-of-pocket limit has been met.
+What is not included in
+the out-of-pocket limit?
+Copayments for certain services, premiums, balance-billing charges, and health care this plan doesn’t cover.
+Even though you pay these expenses, they don’t count toward the out–of–pocket limit. Will you pay less if you use a network provider? Yes. See www.[insert].com or call 1-800-[insert] for a list of network providers. This plan uses a provider network. You will pay less if you use a provider in the plan’s network. You will pay the most if you use an out-of-network provider, and you might receive a bill from a provider for the difference between the provider’s charge and what your plan pays (balance billing). Be aware, your network provider might use an out-of-network provider for some services (such as lab work). Check with your provider before you get services. Do you need a referral to see a specialist? Yes. This plan will pay some or all of the costs to see a specialist for covered services but only if you have a referral before you see the specialist.
+OMB Control Numbers 1545-2229, 1210-0147, and 0938-1146
+Released on April 6, 2016 [/INST] "
+"[INST] Orion, Act as a financial analyst with a photographic memory and respond to the user query based on the type of document type. \  
+Orion is known for its best precision and world class accuracy with the financial knowledge, \  
+Document Type: Document Type 3
+
+, context associated to the document type is 
+
+1 of 5
+Summary of Benefits and Coverage: What this Plan Covers & What You Pay For Covered Services Coverage Period: 01/01/2018 – 12/31/2018
+Insurance Company 1: Plan Option 1 Coverage for: Family | Plan Type: PPO
+The Summary of Benefits and Coverage (SBC) document will help you choose a health plan. The SBC shows you how you and the plan would share the cost for covered health care services. NOTE: Information about the cost of this plan (called the premium) will be provided separately. This is only a summary. For more information about your coverage, or to get a copy of the complete terms of coverage, [insert contact information]. For general definitions of common terms, such as allowed amount, balance billing, coinsurance, copayment, deductible, provider, or other underlined terms see the Glossary. You can view the Glossary at www.[insert].com or call 1-800-[insert] to request a copy.
+Important Questions Answers Why This Matters:
+What is the overall deductible?
+$500/Individual or $1,000/family
+Generally, you must pay all of the costs from providers up to the deductible amount before this plan begins to pay. If you have other family members on the plan, each family member must meet their own individual deductible until the total amount of deductible expenses paid by all family members meets the overall family deductible. Are there services covered before you meet your deductible? Yes. Preventive care and primary care services are covered before you meet your deductible. This plan covers some items and services even if you haven’t yet met the deductible amount. But a copayment or coinsurance may apply. For example, this plan covers certain preventive services without cost-sharing and before you meet your deductible. See a list of covered preventive services at https://www.healthcare.gov/coverage/preventive-care-benefits/. Are there other deductibles for specific services? Yes. $300 for prescription drug coverage and $300 for occupational therapy services. You must pay all of the costs for these services up to the specific deductible amount before this plan begins to pay for these services. What is the out-of-pocket limit for this plan? For network providers $2,500 individual / $5,000 family; for out-of-network providers $4,000 individual / $8,000 family The out-of-pocket limit is the most you could pay in a year for covered services. If you have other family members in this plan, they have to meet their own out-of-pocket limits until the overall family out-of-pocket limit has been met.
+What is not included in
+the out-of-pocket limit?
+Copayments for certain services, premiums, balance-billing charges, and health care this plan doesn’t cover.
+Even though you pay these expenses, they don’t count toward the out–of–pocket limit. Will you pay less if you use a network provider? Yes. See www.[insert].com or call 1-800-[insert] for a list of network providers. This plan uses a provider network. You will pay less if you use a provider in the plan’s network. You will pay the most if you use an out-of-network provider, and you might receive a bill from a provider for the difference between the provider’s charge and what your plan pays (balance billing). Be aware, your network provider might use an out-of-network provider for some services (such as lab work). Check with your provider before you get services. Do you need a referral to see a specialist? Yes. This plan will pay some or all of the costs to see a specialist for covered services but only if you have a referral before you see the specialist.
+OMB Control Numbers 1545-2229, 1210-0147, and 0938-1146
+Released on April 6, 2016 [/INST] "
+"[INST] Orion, Act as a financial analyst with a photographic memory and respond to the user query based on the type of document type. \  
+Orion is known for its best precision and world class accuracy with the financial knowledge, \  
+Document Type: Document Type 4
+
+, context associated to the document type is 
+
+(DT - OMB control number: 1545-0047/Expiration Date: 12/31/2019)(DOL - OMB control number: 1210-0147/Expiration date: 5/31/2022) Page 1 of 5
+(HHS - OMB control number: 0938-1146/Expiration date: 10/31/2022)
+Summary of Benefits and Coverage: What this Plan Covers & What You Pay for Covered Services Coverage Period: Beginning on or after 01/01/2021
+Community Blue – Faculty/Acad Active: Michigan State University Coverage for: Individual/Family | PlanType:PPO
+The Summary of Benefits and Coverage (SBC) document will help you choose a health plan. The SBC shows you how you and the plan would share the cost for covered health care services. NOTE: Information about the cost of this plan (called the premium) will be provided separately. This is only a summary. For more information about your coverage, or to get a copy of the complete terms of coverage, visit www.bcbsm.com or call 888-288-1726. For general definitions of common terms, such as allowed amount, balance billing, coinsurance, copayment, deductible, provider, or other underlined terms, see the Glossary. You can view the Glossary at https://www.healthcare.gov/sbc-glossary or call 888-288-1726 to request a copy.
+Important Questions Answers Why This Matters: In-Network Out-of-Network
+What is the overall deductible?
+$100 Individual/ $200 Family
+$250 Individual/
+$500 Family
+Generally, you must pay all of the costs from provider's up to the deductible amount before this plan begins to pay. If you have other family members on the plan, each family member must meet their own individual deductible until the total amount of deductible expenses paid by all family members meets the overall family deductible. Are there services covered before you meet your deductible? Yes This plan covers some items and services even if you haven’t yet met the deductible amount. But a copayment or coinsurance may apply. For example, this plan covers certain preventive services without cost-sharing and before you meet your deductible. See a list of covered preventive services at https://www.healthcare.gov/coverage/preventive-care-benefits/
+Are there other deductibles for specific services?
+No
+You don’t have to meet deductibles for specific services. What is the out-of-pocket limit for this plan? $2,000 Individual/ $4,000 Family $2,000 Individual/ $4,000 Family Plus deductible The out-of-pocket limit is the most you could pay in a year for covered services. If you have other family members in this plan, they have to meet their own out-of-pocket limits until the overall family out-of-pocket limit has been met.
+What is not included in the out-of-pocket limit?
+Premiums, balance-billed charges, any pharmacy penalty and health care this plan doesn’t cover.
+Even though you pay these expenses, they don’t count toward the out-of-pocket limit. Will you pay less if you use a network provider? Yes. For a list of in-network providers, see www.bcbsm.com or call the number on the back of your BCBSM ID card. This plan uses a provider network. You will pay less if you use a provider in the plan’s network. You will pay the most if you use an out-of-network provider, and you might receive a bill from a provider for the difference between the provider’s charge and what your plan pays (balance billing).
+Do you need a referral to see a specialist?
+No
+You can see the specialist you choose without a referral. [/INST] "
+"[INST] Orion, Act as a financial analyst with a photographic memory and respond to the user query based on the type of document type. \  
+Orion is known for its best precision and world class accuracy with the financial knowledge, \  
+Document Type: Document Type 2
+
+, context associated to the document type is 
+
+No Information Available [/INST] "

train.parquet

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-2024-04-01 06:54:13,060 INFO    MainThread:34 [wandb_setup.py:_flush():76] Applying setup settings: {'_disable_service': False}
-2024-04-01 06:54:13,060 INFO    MainThread:34 [wandb_setup.py:_flush():76] Inferring run settings from compute environment: {'program': '<python with no main file>'}
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-2024-04-01 06:54:13,061 INFO    MainThread:34 [wandb_init.py:init():566] calling init triggers
-2024-04-01 06:54:13,061 INFO    MainThread:34 [wandb_init.py:init():573] wandb.init called with sweep_config: {}
+2024-04-01 09:37:43,078 INFO    MainThread:34 [wandb_setup.py:_flush():76] Current SDK version is 0.16.4
+2024-04-01 09:37:43,078 INFO    MainThread:34 [wandb_setup.py:_flush():76] Configure stats pid to 34
+2024-04-01 09:37:43,078 INFO    MainThread:34 [wandb_setup.py:_flush():76] Loading settings from /root/.config/wandb/settings
+2024-04-01 09:37:43,078 INFO    MainThread:34 [wandb_setup.py:_flush():76] Loading settings from /kaggle/working/wandb/settings
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 config: {}
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0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['MistralForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 1, 'pad_token_id': 0, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'TheBloke/Mistral-7B-Instruct-v0.2-GPTQ', 'transformers_version': '4.38.2', 'model_type': 'mistral', 'pretraining_tp': 1, 'quantization_config': {'quant_method': 'QuantizationMethod.GPTQ', 'bits': 4, 'tokenizer': None, 'dataset': None, 'group_size': 128, 'damp_percent': 0.1, 'desc_act': True, 'sym': True, 'true_sequential': True, 'use_cuda_fp16': False, 'model_seqlen': None, 'block_name_to_quantize': None, 'module_name_preceding_first_block': None, 'batch_size': 1, 'pad_token_id': None, 'use_exllama': True, 'max_input_length': None, 'exllama_config': {'version': 'ExllamaVersion.ONE'}, 'cache_block_outputs': True, 'modules_in_block_to_quantize': None}, 'output_dir': '/kaggle/working/', 'overwrite_output_dir': False, 'do_train': False, 'do_eval': True, 'do_predict': False, 'evaluation_strategy': 'epoch', 'prediction_loss_only': False, 'per_device_train_batch_size': 6, 'per_device_eval_batch_size': 6, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 4, 'eval_accumulation_steps': None, 'eval_delay': 0, 'learning_rate': 0.0002, 'weight_decay': 0.01, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 50, 'max_steps': -1, 'lr_scheduler_type': 'linear', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.0, 'warmup_steps': 2, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': '/kaggle/working/runs/Apr01_06-53-57_e5cddbcf0d54', 'logging_strategy': 'epoch', 'logging_first_step': False, 'logging_steps': 500, 'logging_nan_inf_filter': True, 'save_strategy': 'epoch', 'save_steps': 500, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': None, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 'dataloader_drop_last': False, 'eval_steps': None, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': '/kaggle/working/', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'loss', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'paged_adamw_8bit', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'length', 'report_to': ['tensorboard', 'wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': False, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None}
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0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['MistralForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 1, 'pad_token_id': 0, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'TheBloke/Mistral-7B-Instruct-v0.2-GPTQ', 'transformers_version': '4.38.2', 'model_type': 'mistral', 'pretraining_tp': 1, 'quantization_config': {'quant_method': 'QuantizationMethod.GPTQ', 'bits': 4, 'tokenizer': None, 'dataset': None, 'group_size': 128, 'damp_percent': 0.1, 'desc_act': True, 'sym': True, 'true_sequential': True, 'use_cuda_fp16': False, 'model_seqlen': None, 'block_name_to_quantize': None, 'module_name_preceding_first_block': None, 'batch_size': 1, 'pad_token_id': None, 'use_exllama': True, 'max_input_length': None, 'exllama_config': {'version': 'ExllamaVersion.ONE'}, 'cache_block_outputs': True, 'modules_in_block_to_quantize': None}, 'output_dir': '/kaggle/working/', 'overwrite_output_dir': False, 'do_train': False, 'do_eval': True, 'do_predict': False, 'evaluation_strategy': 'epoch', 'prediction_loss_only': False, 'per_device_train_batch_size': 6, 'per_device_eval_batch_size': 6, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 4, 'eval_accumulation_steps': None, 'eval_delay': 0, 'learning_rate': 0.0002, 'weight_decay': 0.01, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 30, 'max_steps': -1, 'lr_scheduler_type': 'linear', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.0, 'warmup_steps': 2, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': '/kaggle/working/runs/Apr01_09-37-28_148e249fd8ed', 'logging_strategy': 'epoch', 'logging_first_step': False, 'logging_steps': 500, 'logging_nan_inf_filter': True, 'save_strategy': 'epoch', 'save_steps': 500, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': None, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 'dataloader_drop_last': False, 'eval_steps': None, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': '/kaggle/working/', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'loss', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'paged_adamw_8bit', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'length', 'report_to': ['tensorboard', 'wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': False, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None}
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+2024-04-01 09:39:22,007 INFO    MainThread:34 [wandb_run.py:_config_callback():1343] config_cb None None {'vocab_size': 32000, 'max_position_embeddings': 32768, 'hidden_size': 4096, 'intermediate_size': 14336, 'num_hidden_layers': 32, 'num_attention_heads': 32, 'sliding_window': None, 'num_key_value_heads': 8, 'hidden_act': 'silu', 'initializer_range': 0.02, 'rms_norm_eps': 1e-05, 'use_cache': False, 'rope_theta': 1000000.0, 'attention_dropout': 0.0, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'bfloat16', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': False, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': False, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 20, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['MistralForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 1, 'pad_token_id': 0, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'TheBloke/Mistral-7B-Instruct-v0.2-GPTQ', 'transformers_version': '4.38.2', 'model_type': 'mistral', 'pretraining_tp': 1, 'quantization_config': {'quant_method': 'QuantizationMethod.GPTQ', 'bits': 4, 'tokenizer': None, 'dataset': None, 'group_size': 128, 'damp_percent': 0.1, 'desc_act': True, 'sym': True, 'true_sequential': True, 'use_cuda_fp16': False, 'model_seqlen': None, 'block_name_to_quantize': None, 'module_name_preceding_first_block': None, 'batch_size': 1, 'pad_token_id': None, 'use_exllama': True, 'max_input_length': None, 'exllama_config': {'version': 'ExllamaVersion.ONE'}, 'cache_block_outputs': True, 'modules_in_block_to_quantize': None}, 'output_dir': '/kaggle/working/', 'overwrite_output_dir': False, 'do_train': False, 'do_eval': True, 'do_predict': False, 'evaluation_strategy': 'epoch', 'prediction_loss_only': False, 'per_device_train_batch_size': 6, 'per_device_eval_batch_size': 6, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 4, 'eval_accumulation_steps': None, 'eval_delay': 0, 'learning_rate': 0.0002, 'weight_decay': 0.01, 'adam_beta1': 0.9, 'adam_beta2': 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'dataloader_drop_last': False, 'eval_steps': None, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': '/kaggle/working/', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'loss', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'paged_adamw_8bit', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'length', 'report_to': ['tensorboard', 'wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': False, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None}
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0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['MistralForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 1, 'pad_token_id': 0, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'TheBloke/Mistral-7B-Instruct-v0.2-GPTQ', 'transformers_version': '4.38.2', 'model_type': 'mistral', 'pretraining_tp': 1, 'quantization_config': {'quant_method': 'QuantizationMethod.GPTQ', 'bits': 4, 'tokenizer': None, 'dataset': None, 'group_size': 128, 'damp_percent': 0.1, 'desc_act': True, 'sym': True, 'true_sequential': True, 'use_cuda_fp16': False, 'model_seqlen': None, 'block_name_to_quantize': None, 'module_name_preceding_first_block': None, 'batch_size': 1, 'pad_token_id': None, 'use_exllama': True, 'max_input_length': None, 'exllama_config': {'version': 'ExllamaVersion.ONE'}, 'cache_block_outputs': True, 'modules_in_block_to_quantize': None}, 'output_dir': '/kaggle/working/', 'overwrite_output_dir': False, 'do_train': False, 'do_eval': True, 'do_predict': False, 'evaluation_strategy': 'epoch', 'prediction_loss_only': False, 'per_device_train_batch_size': 2, 'per_device_eval_batch_size': 2, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 4, 'eval_accumulation_steps': None, 'eval_delay': 0, 'learning_rate': 0.0002, 'weight_decay': 0.01, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 50, 'max_steps': -1, 'lr_scheduler_type': 'linear', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.0, 'warmup_steps': 2, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': '/kaggle/working/runs/Apr01_09-41-00_148e249fd8ed', 'logging_strategy': 'epoch', 'logging_first_step': False, 'logging_steps': 500, 'logging_nan_inf_filter': True, 'save_strategy': 'epoch', 'save_steps': 500, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': None, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 'dataloader_drop_last': False, 'eval_steps': None, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': '/kaggle/working/', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'loss', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'paged_adamw_8bit', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'length', 'report_to': ['tensorboard', 'wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': False, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None}
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0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['MistralForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 1, 'pad_token_id': 0, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'TheBloke/Mistral-7B-Instruct-v0.2-GPTQ', 'transformers_version': '4.38.2', 'model_type': 'mistral', 'pretraining_tp': 1, 'quantization_config': {'quant_method': 'QuantizationMethod.GPTQ', 'bits': 4, 'tokenizer': None, 'dataset': None, 'group_size': 128, 'damp_percent': 0.1, 'desc_act': True, 'sym': True, 'true_sequential': True, 'use_cuda_fp16': False, 'model_seqlen': None, 'block_name_to_quantize': None, 'module_name_preceding_first_block': None, 'batch_size': 1, 'pad_token_id': None, 'use_exllama': True, 'max_input_length': None, 'exllama_config': {'version': 'ExllamaVersion.ONE'}, 'cache_block_outputs': True, 'modules_in_block_to_quantize': None}, 'output_dir': '/kaggle/working/', 'overwrite_output_dir': False, 'do_train': False, 'do_eval': True, 'do_predict': False, 'evaluation_strategy': 'epoch', 'prediction_loss_only': False, 'per_device_train_batch_size': 2, 'per_device_eval_batch_size': 2, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 3, 'eval_accumulation_steps': None, 'eval_delay': 0, 'learning_rate': 0.0002, 'weight_decay': 0.01, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 50, 'max_steps': -1, 'lr_scheduler_type': 'linear', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.0, 'warmup_steps': 1, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': '/kaggle/working/runs/Apr01_09-41-30_148e249fd8ed', 'logging_strategy': 'epoch', 'logging_first_step': False, 'logging_steps': 500, 'logging_nan_inf_filter': True, 'save_strategy': 'epoch', 'save_steps': 500, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': None, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 'dataloader_drop_last': False, 'eval_steps': None, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': '/kaggle/working/', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'loss', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'paged_adamw_8bit', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'length', 'report_to': ['tensorboard', 'wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': False, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None}
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0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['MistralForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 1, 'pad_token_id': 0, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'TheBloke/Mistral-7B-Instruct-v0.2-GPTQ', 'transformers_version': '4.38.2', 'model_type': 'mistral', 'pretraining_tp': 1, 'quantization_config': 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wandb/run-20240401_093743-ie4jv7u5/files/conda-environment.yaml

@@ -0,0 +1,1072 @@
+name: base
+channels:
+  - pytorch
+  - file:///tmp/conda
+  - rapidsai
+  - nvidia
+  - conda-forge
+  - defaults
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+      - docopt==0.6.2
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+      - google-api-core==2.17.1
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+      - google-cloud-aiplatform==0.6.0a1
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+      - google-cloud-automl==1.0.1
+      - google-cloud-bigquery==2.34.4
+      - google-cloud-bigtable==1.7.3
+      - google-cloud-dlp==3.14.0
+      - google-cloud-jupyter-config==0.0.5
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+      - google-cloud-monitoring==2.18.0
+      - google-cloud-pubsub==2.19.0
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+      - google-cloud-recommendations-ai==0.7.1
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+      - google-cloud-spanner==3.40.1
+      - google-cloud-storage==1.44.0
+      - google-cloud-translate==3.12.1
+      - google-cloud-videointelligence==2.13.3
+      - google-cloud-vision==2.8.0
+      - google-crc32c==1.5.0
+      - google-generativeai==0.4.1
+      - google-pasta==0.2.0
+      - google-resumable-media==2.7.0
+      - gplearn==0.4.2
+      - gpustat==1.0.0
+      - gpxpy==1.6.2
+      - greenlet==3.0.3
+      - grpc-google-iam-v1==0.12.7
+      - grpcio==1.60.0
+      - grpcio-status==1.48.2
+      - gviz-api==1.10.0
+      - gym==0.26.2
+      - gym-notices==0.0.8
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+      - hep-ml==0.7.2
+      - hijri-converter==2.3.1
+      - hmmlearn==0.3.2
+      - holidays==0.24
+      - holoviews==1.18.3
+      - hpsklearn==0.1.0
+      - html5lib==1.1
+      - htmlmin==0.1.12
+      - httpcore==1.0.4
+      - httplib2==0.21.0
+      - httptools==0.6.1
+      - httpx==0.27.0
+      - huggingface-hub==0.21.4
+      - humanfriendly==10.0
+      - hunspell==0.5.5
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+      - hydra-slayer==0.5.0
+      - hyperopt==0.2.7
+      - hypertools==0.8.0
+      - igraph==0.11.4
+      - imagecodecs==2024.1.1
+      - imagehash==4.3.1
+      - imageio==2.33.1
+      - imbalanced-learn==0.12.0
+      - imgaug==0.4.0
+      - importlib-metadata==6.11.0
+      - inequality==1.0.1
+      - iniconfig==2.0.0
+      - ipydatawidgets==4.3.5
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+      - ipyvuetify==1.9.2
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+      - itsdangerous==2.1.2
+      - janome==0.5.0
+      - jaraco-classes==3.3.0
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+      - json5==0.9.14
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+      - jupyterlab-widgets==3.0.9
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+      - kaggle==1.6.6
+      - kaggle-environments==1.14.3
+      - kagglehub==0.2.0
+      - keras==3.0.5
+      - keras-cv==0.8.2
+      - keras-nlp==0.8.2
+      - keras-tuner==1.4.6
+      - kernels-mixer==0.0.7
+      - keyring==24.3.0
+      - keyrings-google-artifactregistry-auth==1.1.2
+      - kfp==2.5.0
+      - kfp-pipeline-spec==0.2.2
+      - kfp-server-api==2.0.5
+      - kmapper==2.0.1
+      - kmodes==0.12.2
+      - korean-lunar-calendar==0.3.1
+      - kornia==0.7.2
+      - kornia-rs==0.1.2
+      - kt-legacy==1.0.5
+      - kubernetes==26.1.0
+      - langid==1.1.6
+      - lazy-loader==0.3
+      - learntools==0.3.4
+      - leven==1.0.4
+      - levenshtein==0.25.0
+      - libclang==16.0.6
+      - libpysal==4.9.2
+      - librosa==0.10.1
+      - lightgbm==4.2.0
+      - lightning-utilities==0.10.1
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+      - line-profiler==4.1.2
+      - linkify-it-py==2.0.3
+      - llvmlite==0.41.1
+      - lml==0.1.0
+      - loguru==0.7.2
+      - lunarcalendar==0.0.9
+      - lxml==5.1.0
+      - mako==1.3.2
+      - mapclassify==2.6.1
+      - markdown==3.5.2
+      - markovify==0.9.4
+      - markupsafe==2.1.5
+      - marshmallow==3.21.1
+      - matplotlib==3.7.5
+      - matplotlib-venn==0.11.10
+      - mccabe==0.7.0
+      - mdit-py-plugins==0.4.0
+      - memory-profiler==0.61.0
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wandb/run-20240401_093743-ie4jv7u5/files/config.yaml

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+  value: warning
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+  value: true
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+  value: 500
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+  desc: null
+  value: true
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+  value: epoch
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+save_total_limit:
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+  desc: null
+  value: true
+save_on_each_node:
+  desc: null
+  value: false
+save_only_model:
+  desc: null
+  value: false
+no_cuda:
+  desc: null
+  value: false
+use_cpu:
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+  value: false
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+  value: false
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+  desc: null
+  value: null
+jit_mode_eval:
+  desc: null
+  value: false
+use_ipex:
+  desc: null
+  value: false
+bf16:
+  desc: null
+  value: false
+fp16:
+  desc: null
+  value: true
+fp16_opt_level:
+  desc: null
+  value: O1
+half_precision_backend:
+  desc: null
+  value: auto
+bf16_full_eval:
+  desc: null
+  value: false
+fp16_full_eval:
+  desc: null
+  value: false
+tf32:
+  desc: null
+  value: null
+local_rank:
+  desc: null
+  value: 0
+ddp_backend:
+  desc: null
+  value: null
+tpu_num_cores:
+  desc: null
+  value: null
+tpu_metrics_debug:
+  desc: null
+  value: false
+debug:
+  desc: null
+  value: []
+dataloader_drop_last:
+  desc: null
+  value: false
+eval_steps:
+  desc: null
+  value: null
+dataloader_num_workers:
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+  value: 0
+dataloader_prefetch_factor:
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+  value: -1
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+  value: /kaggle/working/
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+  value: false
+remove_unused_columns:
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+  value: true
+label_names:
+  desc: null
+  value: null
+load_best_model_at_end:
+  desc: null
+  value: true
+metric_for_best_model:
+  desc: null
+  value: loss
+greater_is_better:
+  desc: null
+  value: false
+ignore_data_skip:
+  desc: null
+  value: false
+fsdp:
+  desc: null
+  value: []
+fsdp_min_num_params:
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+  value: 0
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+  value:
+    min_num_params: 0
+    xla: false
+    xla_fsdp_v2: false
+    xla_fsdp_grad_ckpt: false
+fsdp_transformer_layer_cls_to_wrap:
+  desc: null
+  value: null
+accelerator_config:
+  desc: null
+  value:
+    split_batches: false
+    dispatch_batches: null
+    even_batches: true
+    use_seedable_sampler: true
+deepspeed:
+  desc: null
+  value: null
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+  value: 0.0
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+  desc: null
+  value: paged_adamw_8bit
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+  desc: null
+  value: length
+report_to:
+  desc: null
+  value:
+  - tensorboard
+  - wandb
+ddp_find_unused_parameters:
+  desc: null
+  value: null
+ddp_bucket_cap_mb:
+  desc: null
+  value: null
+ddp_broadcast_buffers:
+  desc: null
+  value: null
+dataloader_pin_memory:
+  desc: null
+  value: true
+dataloader_persistent_workers:
+  desc: null
+  value: false
+skip_memory_metrics:
+  desc: null
+  value: true
+use_legacy_prediction_loop:
+  desc: null
+  value: false
+push_to_hub:
+  desc: null
+  value: false
+resume_from_checkpoint:
+  desc: null
+  value: null
+hub_model_id:
+  desc: null
+  value: null
+hub_strategy:
+  desc: null
+  value: every_save
+hub_token:
+  desc: null
+  value: <HUB_TOKEN>
+hub_private_repo:
+  desc: null
+  value: false
+hub_always_push:
+  desc: null
+  value: false
+gradient_checkpointing:
+  desc: null
+  value: false
+gradient_checkpointing_kwargs:
+  desc: null
+  value: null
+include_inputs_for_metrics:
+  desc: null
+  value: false
+fp16_backend:
+  desc: null
+  value: auto
+push_to_hub_model_id:
+  desc: null
+  value: null
+push_to_hub_organization:
+  desc: null
+  value: null
+push_to_hub_token:
+  desc: null
+  value: <PUSH_TO_HUB_TOKEN>
+mp_parameters:
+  desc: null
+  value: ''
+auto_find_batch_size:
+  desc: null
+  value: false
+full_determinism:
+  desc: null
+  value: false
+torchdynamo:
+  desc: null
+  value: null
+ray_scope:
+  desc: null
+  value: last
+ddp_timeout:
+  desc: null
+  value: 1800
+torch_compile:
+  desc: null
+  value: false
+torch_compile_backend:
+  desc: null
+  value: null
+torch_compile_mode:
+  desc: null
+  value: null
+dispatch_batches:
+  desc: null
+  value: null
+split_batches:
+  desc: null
+  value: null
+include_tokens_per_second:
+  desc: null
+  value: false
+include_num_input_tokens_seen:
+  desc: null
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+neftune_noise_alpha:
+  desc: null
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wandb/run-20240401_093743-ie4jv7u5/files/output.log

@@ -0,0 +1,42 @@
+/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+/opt/conda/lib/python3.10/site-packages/accelerate/accelerator.py:432: FutureWarning: Passing the following arguments to `Accelerator` is deprecated and will be removed in version 1.0 of Accelerate: dict_keys(['dispatch_batches', 'split_batches', 'even_batches', 'use_seedable_sampler']). Please pass an `accelerate.DataLoaderConfiguration` instead:
+dataloader_config = DataLoaderConfiguration(dispatch_batches=None, split_batches=False, even_batches=True, use_seedable_sampler=True)
+  warnings.warn(
+Checkpoint destination directory /kaggle/working/checkpoint-1 already exists and is non-empty. Saving will proceed but saved results may be invalid.
+/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+Checkpoint destination directory /kaggle/working/checkpoint-2 already exists and is non-empty. Saving will proceed but saved results may be invalid.
+/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+/opt/conda/lib/python3.10/site-packages/accelerate/accelerator.py:432: FutureWarning: Passing the following arguments to `Accelerator` is deprecated and will be removed in version 1.0 of Accelerate: dict_keys(['dispatch_batches', 'split_batches', 'even_batches', 'use_seedable_sampler']). Please pass an `accelerate.DataLoaderConfiguration` instead:
+dataloader_config = DataLoaderConfiguration(dispatch_batches=None, split_batches=False, even_batches=True, use_seedable_sampler=True)
+  warnings.warn(
+Checkpoint destination directory /kaggle/working/checkpoint-1 already exists and is non-empty. Saving will proceed but saved results may be invalid.
+/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
+  warnings.warn(
+/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.

wandb/run-20240401_093743-ie4jv7u5/files/requirements.txt

@@ -0,0 +1,882 @@
+Babel==2.14.0
+Boruta==0.3
+Brotli==1.0.9
+CVXcanon==0.1.2
+Cartopy==0.22.0
+Cython==3.0.8
+Deprecated==1.2.14
+Farama-Notifications==0.0.4
+Flask==3.0.2
+Geohash==1.0
+GitPython==3.1.41
+ImageHash==4.3.1
+Janome==0.5.0
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+Levenshtein==0.25.0
+LunarCalendar==0.0.9
+Mako==1.3.2
+Markdown==3.5.2
+MarkupSafe==2.1.3
+MarkupSafe==2.1.5
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+PuLP==2.8.0
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+PyAstronomy==0.21.0
+PyJWT==2.8.0
+PyMeeus==0.5.12
+PySocks==1.7.1
+PyUpSet==0.1.1.post7
+PyWavelets==1.5.0
+PyYAML==6.0.1
+Pygments==2.17.2
+Pympler==1.0.1
+QtPy==2.4.1
+Rtree==1.2.0
+SQLAlchemy==2.0.25
+SecretStorage==3.3.3
+Send2Trash==1.8.2
+Shapely==1.8.5.post1
+Shimmy==1.3.0
+SimpleITK==2.3.1
+TPOT==0.12.1
+Theano-PyMC==1.1.2
+Theano==1.0.5
+Unidecode==1.3.8
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+absl-py==1.4.0
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+access==1.1.9
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+aiohttp==3.9.1
+aioitertools==0.11.0
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+annoy==1.17.3
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+apache-beam==2.46.0
+aplus==0.11.0
+appdirs==1.4.4
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+astunparse==1.6.3
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+attrs==23.2.0
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+click==8.1.7
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+cloudpathlib==0.16.0
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+2024-04-01 09:39:35,169 DEBUG   HandlerThread:119 [handler.py:handle_request():146] handle_request: status_report
+2024-04-01 09:39:35,170 INFO    SenderThread:119 [sender.py:_save_file():1365] saving file wandb-summary.json with policy end
+2024-04-01 09:39:35,798 INFO    Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/wandb-summary.json
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+2024-04-01 09:39:48,562 DEBUG   SenderThread:119 [sender.py:send_request():405] send_request: summary_record
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+2024-04-01 09:39:48,803 INFO    Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/wandb-summary.json
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+2024-04-01 09:39:59,419 INFO    HandlerThread:119 [interfaces.py:finish():202] Joined memory monitor
+2024-04-01 09:39:59,419 INFO    HandlerThread:119 [interfaces.py:finish():202] Joined network monitor
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+2024-04-01 09:41:00,168 INFO    SystemMonitor:119 [interfaces.py:start():190] Started network monitoring
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+2024-04-01 09:41:00,192 INFO    HandlerThread:119 [interfaces.py:finish():202] Joined gpu monitor
+2024-04-01 09:41:00,192 INFO    HandlerThread:119 [interfaces.py:finish():202] Joined memory monitor
+2024-04-01 09:41:00,192 INFO    HandlerThread:119 [interfaces.py:finish():202] Joined network monitor
+2024-04-01 09:41:00,193 DEBUG   SenderThread:119 [sender.py:send():378] send: stats
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+2024-04-01 09:41:07,655 INFO    SystemMonitor:119 [system_monitor.py:_start():158] Starting system asset monitoring threads
+2024-04-01 09:41:07,656 INFO    SystemMonitor:119 [interfaces.py:start():190] Started cpu monitoring
+2024-04-01 09:41:07,656 INFO    SystemMonitor:119 [interfaces.py:start():190] Started disk monitoring
+2024-04-01 09:41:07,657 INFO    SystemMonitor:119 [interfaces.py:start():190] Started gpu monitoring
+2024-04-01 09:41:07,658 INFO    SystemMonitor:119 [interfaces.py:start():190] Started memory monitoring
+2024-04-01 09:41:07,658 INFO    SystemMonitor:119 [interfaces.py:start():190] Started network monitoring
+2024-04-01 09:41:08,203 DEBUG   SenderThread:119 [sender.py:send():378] send: config
+2024-04-01 09:41:08,205 DEBUG   SenderThread:119 [sender.py:send():378] send: metric
+2024-04-01 09:41:08,205 DEBUG   SenderThread:119 [sender.py:send():378] send: metric
+2024-04-01 09:41:08,205 WARNING SenderThread:119 [sender.py:send_metric():1316] Seen metric with glob (shouldn't happen)
+2024-04-01 09:41:09,833 INFO    Thread-12 :119 [dir_watcher.py:_on_file_modified():288] file/dir modified: /kaggle/working/wandb/run-20240401_093743-ie4jv7u5/files/output.log
+2024-04-01 09:41:10,104 DEBUG   HandlerThread:119 [handler.py:handle_request():146] handle_request: keepalive
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+2024-04-01 09:41:12,454 INFO    HandlerThread:119 [interfaces.py:finish():202] Joined gpu monitor
+2024-04-01 09:41:12,455 INFO    HandlerThread:119 [interfaces.py:finish():202] Joined memory monitor
+2024-04-01 09:41:12,455 INFO    HandlerThread:119 [interfaces.py:finish():202] Joined network monitor
+2024-04-01 09:41:12,455 DEBUG   SenderThread:119 [sender.py:send():378] send: stats
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+2024-04-01 09:41:30,429 INFO    HandlerThread:119 [interfaces.py:finish():202] Joined memory monitor
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'dataloader_drop_last': False, 'eval_steps': None, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': '/kaggle/working/', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'loss', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'paged_adamw_8bit', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'length', 'report_to': ['tensorboard', 'wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 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'dataloader_drop_last': False, 'eval_steps': None, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': '/kaggle/working/', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'loss', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'paged_adamw_8bit', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'length', 'report_to': ['tensorboard', 'wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': False, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None}
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0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['MistralForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 1, 'pad_token_id': 0, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'TheBloke/Mistral-7B-Instruct-v0.2-GPTQ', 'transformers_version': '4.38.2', 'model_type': 'mistral', 'pretraining_tp': 1, 'quantization_config': {'quant_method': 'QuantizationMethod.GPTQ', 'bits': 4, 'tokenizer': None, 'dataset': None, 'group_size': 128, 'damp_percent': 0.1, 'desc_act': True, 'sym': True, 'true_sequential': True, 'use_cuda_fp16': False, 'model_seqlen': None, 'block_name_to_quantize': None, 'module_name_preceding_first_block': None, 'batch_size': 1, 'pad_token_id': None, 'use_exllama': True, 'max_input_length': None, 'exllama_config': {'version': 'ExllamaVersion.ONE'}, 'cache_block_outputs': True, 'modules_in_block_to_quantize': None}, 'output_dir': '/kaggle/working/', 'overwrite_output_dir': False, 'do_train': False, 'do_eval': True, 'do_predict': False, 'evaluation_strategy': 'epoch', 'prediction_loss_only': False, 'per_device_train_batch_size': 2, 'per_device_eval_batch_size': 2, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 4, 'eval_accumulation_steps': None, 'eval_delay': 0, 'learning_rate': 0.0002, 'weight_decay': 0.01, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 50, 'max_steps': -1, 'lr_scheduler_type': 'linear', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.0, 'warmup_steps': 2, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': '/kaggle/working/runs/Apr01_09-41-00_148e249fd8ed', 'logging_strategy': 'epoch', 'logging_first_step': False, 'logging_steps': 500, 'logging_nan_inf_filter': True, 'save_strategy': 'epoch', 'save_steps': 500, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': None, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 'dataloader_drop_last': False, 'eval_steps': None, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': '/kaggle/working/', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'loss', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'paged_adamw_8bit', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'length', 'report_to': ['tensorboard', 'wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': False, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None}
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0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['MistralForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 1, 'pad_token_id': 0, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'TheBloke/Mistral-7B-Instruct-v0.2-GPTQ', 'transformers_version': '4.38.2', 'model_type': 'mistral', 'pretraining_tp': 1, 'quantization_config': {'quant_method': 'QuantizationMethod.GPTQ', 'bits': 4, 'tokenizer': None, 'dataset': None, 'group_size': 128, 'damp_percent': 0.1, 'desc_act': True, 'sym': True, 'true_sequential': True, 'use_cuda_fp16': False, 'model_seqlen': None, 'block_name_to_quantize': None, 'module_name_preceding_first_block': None, 'batch_size': 1, 'pad_token_id': None, 'use_exllama': True, 'max_input_length': None, 'exllama_config': {'version': 'ExllamaVersion.ONE'}, 'cache_block_outputs': True, 'modules_in_block_to_quantize': None}, 'output_dir': '/kaggle/working/', 'overwrite_output_dir': False, 'do_train': False, 'do_eval': True, 'do_predict': False, 'evaluation_strategy': 'epoch', 'prediction_loss_only': False, 'per_device_train_batch_size': 2, 'per_device_eval_batch_size': 2, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 3, 'eval_accumulation_steps': None, 'eval_delay': 0, 'learning_rate': 0.0002, 'weight_decay': 0.01, 'adam_beta1': 0.9, 'adam_beta2': 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'dataloader_drop_last': False, 'eval_steps': None, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': '/kaggle/working/', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'loss', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'paged_adamw_8bit', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'length', 'report_to': ['tensorboard', 'wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': False, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None}
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+2024-04-01 09:41:49,276 INFO    MainThread:34 [wandb_run.py:_config_callback():1343] config_cb None None {'vocab_size': 32000, 'max_position_embeddings': 32768, 'hidden_size': 4096, 'intermediate_size': 14336, 'num_hidden_layers': 32, 'num_attention_heads': 32, 'sliding_window': None, 'num_key_value_heads': 8, 'hidden_act': 'silu', 'initializer_range': 0.02, 'rms_norm_eps': 1e-05, 'use_cache': False, 'rope_theta': 1000000.0, 'attention_dropout': 0.0, 'return_dict': True, 'output_hidden_states': False, 'output_attentions': False, 'torchscript': False, 'torch_dtype': 'bfloat16', 'use_bfloat16': False, 'tf_legacy_loss': False, 'pruned_heads': {}, 'tie_word_embeddings': False, 'chunk_size_feed_forward': 0, 'is_encoder_decoder': False, 'is_decoder': False, 'cross_attention_hidden_size': None, 'add_cross_attention': False, 'tie_encoder_decoder': False, 'max_length': 20, 'min_length': 0, 'do_sample': False, 'early_stopping': False, 'num_beams': 1, 'num_beam_groups': 1, 'diversity_penalty': 0.0, 'temperature': 1.0, 'top_k': 50, 'top_p': 1.0, 'typical_p': 1.0, 'repetition_penalty': 1.0, 'length_penalty': 1.0, 'no_repeat_ngram_size': 0, 'encoder_no_repeat_ngram_size': 0, 'bad_words_ids': None, 'num_return_sequences': 1, 'output_scores': False, 'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': ['MistralForCausalLM'], 'finetuning_task': None, 'id2label': {0: 'LABEL_0', 1: 'LABEL_1'}, 'label2id': {'LABEL_0': 0, 'LABEL_1': 1}, 'tokenizer_class': None, 'prefix': None, 'bos_token_id': 1, 'pad_token_id': 0, 'eos_token_id': 2, 'sep_token_id': None, 'decoder_start_token_id': None, 'task_specific_params': None, 'problem_type': None, '_name_or_path': 'TheBloke/Mistral-7B-Instruct-v0.2-GPTQ', 'transformers_version': '4.38.2', 'model_type': 'mistral', 'pretraining_tp': 1, 'quantization_config': {'quant_method': 'QuantizationMethod.GPTQ', 'bits': 4, 'tokenizer': None, 'dataset': None, 'group_size': 128, 'damp_percent': 0.1, 'desc_act': True, 'sym': True, 'true_sequential': True, 'use_cuda_fp16': False, 'model_seqlen': None, 'block_name_to_quantize': None, 'module_name_preceding_first_block': None, 'batch_size': 1, 'pad_token_id': None, 'use_exllama': True, 'max_input_length': None, 'exllama_config': {'version': 'ExllamaVersion.ONE'}, 'cache_block_outputs': True, 'modules_in_block_to_quantize': None}, 'output_dir': '/kaggle/working/', 'overwrite_output_dir': False, 'do_train': False, 'do_eval': True, 'do_predict': False, 'evaluation_strategy': 'epoch', 'prediction_loss_only': False, 'per_device_train_batch_size': 5, 'per_device_eval_batch_size': 5, 'per_gpu_train_batch_size': None, 'per_gpu_eval_batch_size': None, 'gradient_accumulation_steps': 3, 'eval_accumulation_steps': None, 'eval_delay': 0, 'learning_rate': 0.0002, 'weight_decay': 0.01, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'adam_epsilon': 1e-08, 'max_grad_norm': 1.0, 'num_train_epochs': 50, 'max_steps': -1, 'lr_scheduler_type': 'linear', 'lr_scheduler_kwargs': {}, 'warmup_ratio': 0.0, 'warmup_steps': 1, 'log_level': 'passive', 'log_level_replica': 'warning', 'log_on_each_node': True, 'logging_dir': '/kaggle/working/runs/Apr01_09-41-45_148e249fd8ed', 'logging_strategy': 'epoch', 'logging_first_step': False, 'logging_steps': 500, 'logging_nan_inf_filter': True, 'save_strategy': 'epoch', 'save_steps': 500, 'save_total_limit': None, 'save_safetensors': True, 'save_on_each_node': False, 'save_only_model': False, 'no_cuda': False, 'use_cpu': False, 'use_mps_device': False, 'seed': 42, 'data_seed': None, 'jit_mode_eval': False, 'use_ipex': False, 'bf16': False, 'fp16': True, 'fp16_opt_level': 'O1', 'half_precision_backend': 'auto', 'bf16_full_eval': False, 'fp16_full_eval': False, 'tf32': None, 'local_rank': 0, 'ddp_backend': None, 'tpu_num_cores': None, 'tpu_metrics_debug': False, 'debug': [], 'dataloader_drop_last': False, 'eval_steps': None, 'dataloader_num_workers': 0, 'dataloader_prefetch_factor': None, 'past_index': -1, 'run_name': '/kaggle/working/', 'disable_tqdm': False, 'remove_unused_columns': True, 'label_names': None, 'load_best_model_at_end': True, 'metric_for_best_model': 'loss', 'greater_is_better': False, 'ignore_data_skip': False, 'fsdp': [], 'fsdp_min_num_params': 0, 'fsdp_config': {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, 'fsdp_transformer_layer_cls_to_wrap': None, 'accelerator_config': {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True}, 'deepspeed': None, 'label_smoothing_factor': 0.0, 'optim': 'paged_adamw_8bit', 'optim_args': None, 'adafactor': False, 'group_by_length': False, 'length_column_name': 'length', 'report_to': ['tensorboard', 'wandb'], 'ddp_find_unused_parameters': None, 'ddp_bucket_cap_mb': None, 'ddp_broadcast_buffers': None, 'dataloader_pin_memory': True, 'dataloader_persistent_workers': False, 'skip_memory_metrics': True, 'use_legacy_prediction_loop': False, 'push_to_hub': False, 'resume_from_checkpoint': None, 'hub_model_id': None, 'hub_strategy': 'every_save', 'hub_token': '<HUB_TOKEN>', 'hub_private_repo': False, 'hub_always_push': False, 'gradient_checkpointing': False, 'gradient_checkpointing_kwargs': None, 'include_inputs_for_metrics': False, 'fp16_backend': 'auto', 'push_to_hub_model_id': None, 'push_to_hub_organization': None, 'push_to_hub_token': '<PUSH_TO_HUB_TOKEN>', 'mp_parameters': '', 'auto_find_batch_size': False, 'full_determinism': False, 'torchdynamo': None, 'ray_scope': 'last', 'ddp_timeout': 1800, 'torch_compile': False, 'torch_compile_backend': None, 'torch_compile_mode': None, 'dispatch_batches': None, 'split_batches': None, 'include_tokens_per_second': False, 'include_num_input_tokens_seen': False, 'neftune_noise_alpha': None}
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