Charlie-Han-01
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Browse files- .gitattributes +1 -0
- README.md +46 -0
- adapter_config.json +31 -0
- adapter_model.safetensors +3 -0
- runs/Nov14_02-21-47_r-charlie-han-01-bloom-7b-ziubtl5n-99e9b-dpxh1/events.out.tfevents.1731550938.r-charlie-han-01-bloom-7b-ziubtl5n-99e9b-dpxh1.122.0 +2 -2
- special_tokens_map.json +30 -0
- tokenizer.json +3 -0
- tokenizer_config.json +48 -0
- training_args.bin +3 -0
- training_params.json +49 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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tags:
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- autotrain
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- text-generation-inference
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- text-generation
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- peft
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library_name: transformers
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base_model: bigscience/bloom-7b1
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widget:
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- messages:
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- role: user
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content: What is your favorite condiment?
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license: other
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---
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# Model Trained Using AutoTrain
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This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain).
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# Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_path = "PATH_TO_THIS_REPO"
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tokenizer = AutoTokenizer.from_pretrained(model_path)
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model = AutoModelForCausalLM.from_pretrained(
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model_path,
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device_map="auto",
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torch_dtype='auto'
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).eval()
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# Prompt content: "hi"
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messages = [
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{"role": "user", "content": "hi"}
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]
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input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
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output_ids = model.generate(input_ids.to('cuda'))
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response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
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# Model response: "Hello! How can I assist you today?"
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print(response)
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```
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "bigscience/bloom-7b1",
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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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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"dense",
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"dense_4h_to_h",
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"dense_h_to_4h",
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"query_key_value"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:b01ad25968f58e474ede3f42eb6f3103ea3e803f06471f8f5e8f7a5d4abf7238
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size 8340179480
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runs/Nov14_02-21-47_r-charlie-han-01-bloom-7b-ziubtl5n-99e9b-dpxh1/events.out.tfevents.1731550938.r-charlie-han-01-bloom-7b-ziubtl5n-99e9b-dpxh1.122.0
CHANGED
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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oid sha256:d31f2ccdf18c00c6f98e0c97955aa68671eda208c888ec8377d8d75cfcd0fbc3
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size 7845
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": {
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"content": "<pad>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:d963066d6adae5034a1dc114c3ac444512de09928cf14ed4562ba94d9a440e66
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size 21763085
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tokenizer_config.json
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{
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"add_prefix_space": false,
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"added_tokens_decoder": {
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"0": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"1": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"2": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"3": {
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"content": "<pad>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"bos_token": "<s>",
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"chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
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"clean_up_tokenization_spaces": false,
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"eos_token": "</s>",
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"merges_file": null,
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"model_max_length": 2048,
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"pad_token": "<pad>",
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"padding_side": "right",
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"tokenizer_class": "BloomTokenizer",
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"unk_token": "<unk>",
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"vocab_file": null
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}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:63c8d6db86024c16450c0633d44d87f41e2a6b2877f35998a2516636d8452ab7
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size 5624
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training_params.json
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{
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"model": "bigscience/bloom-7b1",
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"project_name": "Finetuned-BLOOM-7B",
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"data_path": "Finetuned-BLOOM-7B/autotrain-data",
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"train_split": "train",
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"valid_split": null,
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"add_eos_token": true,
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"block_size": 1024,
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"model_max_length": 2048,
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"padding": "right",
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"trainer": "sft",
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"use_flash_attention_2": false,
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"log": "tensorboard",
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"disable_gradient_checkpointing": false,
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"logging_steps": -1,
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"eval_strategy": "epoch",
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"save_total_limit": 1,
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"auto_find_batch_size": false,
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"mixed_precision": "fp16",
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"lr": 3e-05,
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"epochs": 4,
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"batch_size": 3,
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"warmup_ratio": 0.1,
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"gradient_accumulation": 4,
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"optimizer": "adamw_torch",
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"scheduler": "linear",
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"weight_decay": 0.0,
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"max_grad_norm": 1.0,
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"seed": 42,
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"chat_template": "none",
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"quantization": "int4",
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"target_modules": "all-linear",
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"merge_adapter": false,
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"peft": true,
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"lora_r": 16,
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"lora_alpha": 32,
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"lora_dropout": 0.05,
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"model_ref": null,
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"dpo_beta": 0.1,
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"max_prompt_length": 128,
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"max_completion_length": null,
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"prompt_text_column": "autotrain_prompt",
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"text_column": "autotrain_text",
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"rejected_text_column": "autotrain_rejected_text",
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"push_to_hub": true,
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"username": "Charlie-Han-01",
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"unsloth": false,
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"distributed_backend": "ddp"
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}
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