xyzzy
commited on
Commit
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0f52316
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Parent(s):
73e31a3
upload deprecated PEFT adapter model. use for eval only.
Browse files- Backup-2023-08-18/README.md +20 -0
- Backup-2023-08-18/adapter_config.json +21 -0
- Backup-2023-08-18/adapter_model.bin +3 -0
- Backup-2023-08-18/training_parameters.json +30 -0
- Backup-2023-08-18/training_prompt.json +3 -0
- README.md +44 -0
- adapter_config.json +21 -0
- adapter_model.bin +3 -0
- runs/Aug18_21-58-04_DESKTOP-ALJIUJP/events.out.tfevents.1692421084.DESKTOP-ALJIUJP.10890.0 +3 -0
- runs/Aug18_22-09-45_DESKTOP-ALJIUJP/events.out.tfevents.1692421785.DESKTOP-ALJIUJP.467302.0 +3 -0
- training_log.json +16 -0
- training_parameters.json +30 -0
- training_prompt.json +3 -0
Backup-2023-08-18/README.md
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---
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library_name: peft
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---
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- load_in_8bit: True
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- load_in_4bit: False
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- llm_int8_threshold: 6.0
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- llm_int8_skip_modules: None
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- llm_int8_enable_fp32_cpu_offload: False
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- llm_int8_has_fp16_weight: False
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- bnb_4bit_quant_type: fp4
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- bnb_4bit_use_double_quant: False
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- bnb_4bit_compute_dtype: float32
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### Framework versions
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- PEFT 0.5.0.dev0
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Backup-2023-08-18/adapter_config.json
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{
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"auto_mapping": null,
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"base_model_name_or_path": "models/TheBloke_Llama-2-13B-fp16",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layers_pattern": null,
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"layers_to_transform": null,
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"lora_alpha": 512,
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"lora_dropout": 0.05,
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 256,
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"revision": null,
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"target_modules": [
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"q_proj",
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"v_proj"
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],
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"task_type": "CAUSAL_LM"
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}
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Backup-2023-08-18/adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:aef9933db2b706f9f24f378a947ef03fe7742cefe1cae1da3aa06c3d89ddd4e4
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size 419488269
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Backup-2023-08-18/training_parameters.json
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{
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"lora_name": "greener-13-2-base-8bitB",
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"always_override": false,
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"save_steps": 0.0,
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"micro_batch_size": 4,
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"batch_size": 128,
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"epochs": 1.0,
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"learning_rate": "3e-4",
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"lr_scheduler_type": "linear",
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"lora_rank": 256,
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"lora_alpha": 512,
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"lora_dropout": 0.05,
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"cutoff_len": 256,
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"dataset": "None",
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"eval_dataset": "None",
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"format": "None",
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"eval_steps": 100.0,
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"raw_text_file": "greener-pg24246-trim1",
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"overlap_len": 128,
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"newline_favor_len": 128,
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"higher_rank_limit": false,
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"warmup_steps": 100.0,
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"optimizer": "adamw_torch",
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"hard_cut_string": "\\n\\n\\n",
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"train_only_after": "",
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"stop_at_loss": 0,
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"add_eos_token": false,
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"min_chars": 0.0,
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"report_to": "tensorboard"
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}
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Backup-2023-08-18/training_prompt.json
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{
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"template_type": "raw_text"
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}
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README.md
ADDED
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---
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library_name: peft
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---
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## Training procedure
|
5 |
+
|
6 |
+
|
7 |
+
The following `bitsandbytes` quantization config was used during training:
|
8 |
+
- load_in_8bit: True
|
9 |
+
- load_in_4bit: False
|
10 |
+
- llm_int8_threshold: 6.0
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11 |
+
- llm_int8_skip_modules: None
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12 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
13 |
+
- llm_int8_has_fp16_weight: False
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+
- bnb_4bit_quant_type: fp4
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+
- bnb_4bit_use_double_quant: False
|
16 |
+
- bnb_4bit_compute_dtype: float32
|
17 |
+
|
18 |
+
The following `bitsandbytes` quantization config was used during training:
|
19 |
+
- load_in_8bit: True
|
20 |
+
- load_in_4bit: False
|
21 |
+
- llm_int8_threshold: 6.0
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+
- llm_int8_skip_modules: None
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+
- llm_int8_enable_fp32_cpu_offload: False
|
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+
- llm_int8_has_fp16_weight: False
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+
- bnb_4bit_quant_type: fp4
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+
- bnb_4bit_use_double_quant: False
|
27 |
+
- bnb_4bit_compute_dtype: float32
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+
|
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+
The following `bitsandbytes` quantization config was used during training:
|
30 |
+
- load_in_8bit: True
|
31 |
+
- load_in_4bit: False
|
32 |
+
- llm_int8_threshold: 6.0
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+
- llm_int8_skip_modules: None
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+
- llm_int8_enable_fp32_cpu_offload: False
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+
- llm_int8_has_fp16_weight: False
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+
- bnb_4bit_quant_type: fp4
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+
- bnb_4bit_use_double_quant: False
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+
- bnb_4bit_compute_dtype: float32
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### Framework versions
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- PEFT 0.5.0.dev0
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- PEFT 0.5.0.dev0
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- PEFT 0.5.0.dev0
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adapter_config.json
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{
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"auto_mapping": null,
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"base_model_name_or_path": "models/TheBloke_Llama-2-13B-fp16",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layers_pattern": null,
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"layers_to_transform": null,
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"lora_alpha": 512,
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"lora_dropout": 0.05,
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 256,
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"revision": null,
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"target_modules": [
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"q_proj",
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"v_proj"
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],
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"task_type": "CAUSAL_LM"
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}
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adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:5e9323b0e2f29493ec38fa416a7d3e4a18b0edf734cff70838679be45ae61de6
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size 838918733
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runs/Aug18_21-58-04_DESKTOP-ALJIUJP/events.out.tfevents.1692421084.DESKTOP-ALJIUJP.10890.0
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:cd43f71d864559521ac6f86726227f0177cfd42b7f6daa84bc4fc3474784125d
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size 4483
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runs/Aug18_22-09-45_DESKTOP-ALJIUJP/events.out.tfevents.1692421785.DESKTOP-ALJIUJP.467302.0
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:ec4e6b5da85a2e6c165b2a235bf8bdfb0db0237a8e10a67f9738aab541dcd618
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size 5139
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training_log.json
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{
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"base_model_name": "TheBloke_Llama-2-13B-fp16",
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"base_model_class": "LlamaForCausalLM",
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"base_loaded_in_4bit": false,
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"base_loaded_in_8bit": true,
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"projections": "q, v",
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"loss": 2.5449,
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"learning_rate": 0.0001125,
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"epoch": 0.99,
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"current_steps": 383,
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"train_runtime": 604.1501,
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"train_samples_per_second": 2.569,
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"train_steps_per_second": 0.02,
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"total_flos": 3.081650980257792e+16,
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"train_loss": 2.6347402334213257
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}
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training_parameters.json
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{
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"lora_name": "greener-13-2-base-8bitB",
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"always_override": false,
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"save_steps": 0.0,
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"micro_batch_size": 4,
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"batch_size": 128,
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"epochs": 1.0,
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"learning_rate": "3e-4",
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"lr_scheduler_type": "linear",
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"lora_rank": 256,
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"lora_alpha": 512,
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"lora_dropout": 0.05,
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"cutoff_len": 256,
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"dataset": "None",
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"eval_dataset": "None",
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"format": "None",
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"eval_steps": 100.0,
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"raw_text_file": "greener-pg24246-trim1",
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"overlap_len": 128,
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"newline_favor_len": 128,
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"higher_rank_limit": false,
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+
"warmup_steps": 100.0,
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"optimizer": "adamw_torch",
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"hard_cut_string": "\\n\\n\\n",
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"train_only_after": "",
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"stop_at_loss": 0,
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"add_eos_token": false,
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"min_chars": 0.0,
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"report_to": "tensorboard"
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}
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training_prompt.json
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{
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"template_type": "raw_text"
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}
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