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Browse files- README.md +151 -0
- adapter_config.json +33 -0
- adapter_model.bin +3 -0
- checkpoint-256/README.md +202 -0
- checkpoint-256/adapter_config.json +33 -0
- checkpoint-256/adapter_model.safetensors +3 -0
- checkpoint-256/optimizer.pt +3 -0
- checkpoint-256/rng_state_0.pth +3 -0
- checkpoint-256/rng_state_1.pth +3 -0
- checkpoint-256/rng_state_2.pth +3 -0
- checkpoint-256/rng_state_3.pth +3 -0
- checkpoint-256/rng_state_4.pth +3 -0
- checkpoint-256/rng_state_5.pth +3 -0
- checkpoint-256/rng_state_6.pth +3 -0
- checkpoint-256/scheduler.pt +3 -0
- checkpoint-256/special_tokens_map.json +30 -0
- checkpoint-256/tokenizer.json +0 -0
- checkpoint-256/tokenizer_config.json +45 -0
- checkpoint-256/trainer_state.json +1853 -0
- checkpoint-256/training_args.bin +3 -0
- checkpoint-512/README.md +202 -0
- checkpoint-512/adapter_config.json +33 -0
- checkpoint-512/adapter_model.safetensors +3 -0
- checkpoint-512/optimizer.pt +3 -0
- checkpoint-512/rng_state_0.pth +3 -0
- checkpoint-512/rng_state_1.pth +3 -0
- checkpoint-512/rng_state_2.pth +3 -0
- checkpoint-512/rng_state_3.pth +3 -0
- checkpoint-512/rng_state_4.pth +3 -0
- checkpoint-512/rng_state_5.pth +3 -0
- checkpoint-512/rng_state_6.pth +3 -0
- checkpoint-512/scheduler.pt +3 -0
- checkpoint-512/special_tokens_map.json +30 -0
- checkpoint-512/tokenizer.json +0 -0
- checkpoint-512/tokenizer_config.json +45 -0
- checkpoint-512/trainer_state.json +3677 -0
- checkpoint-512/training_args.bin +3 -0
- config.json +44 -0
- runs/Mar26_00-22-15_ginger/events.out.tfevents.1711412537.ginger.170386.0 +3 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer_config.json +45 -0
README.md
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---
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library_name: peft
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tags:
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- generated_from_trainer
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base_model: JY623/KoSOLAR-v2.0
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model-index:
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- name: qlora-out/v1.2
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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<details><summary>See axolotl config</summary>
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axolotl version: `0.4.0`
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```yaml
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base_model: JY623/KoSOLAR-v2.0
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model_type: AutoModelForCausalLM
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tokenizer_type: AutoTokenizer
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load_in_8bit: false
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load_in_4bit: true
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strict: false
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push_dataset_to_hub:
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datasets:
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- path: kyujinpy/KOR-OpenOrca-Platypus-v3
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type: alpaca
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dataset_prepared_path:
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val_set_size: 0.05
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output_dir: ./qlora-out/v1.2
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adapter: qlora
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lora_model_dir:
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+
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sequence_len: 4096
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sample_packing: true
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pad_to_sequence_len: true
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+
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+
lora_r: 32
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lora_alpha: 16
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lora_dropout: 0.05
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+
lora_target_modules:
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lora_target_linear: true
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+
lora_fan_in_fan_out:
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+
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+
wandb_project:
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+
wandb_entity:
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+
wandb_watch:
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+
wandb_name:
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+
wandb_log_model:
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+
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gradient_accumulation_steps: 4
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micro_batch_size: 1
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num_epochs: 2
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optimizer: paged_adamw_32bit
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lr_scheduler: cosine
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learning_rate: 0.0002
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+
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train_on_inputs: false
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group_by_length: false
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bf16: auto
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fp16:
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tf32: false
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gradient_checkpointing: true
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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logging_steps: 1
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xformers_attention:
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flash_attention: false
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+
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warmup_steps: 20
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evals_per_epoch: 4
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eval_table_size:
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saves_per_epoch: 1
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debug:
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deepspeed:
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weight_decay: 0.1
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+
fsdp:
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fsdp_config:
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special_tokens:
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bos_token: "<s>"
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eos_token: "</s>"
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unk_token: "<unk>"
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```
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</details><br>
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# qlora-out/v1.2
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This model is a fine-tuned version of [JY623/KoSOLAR-v2.0](https://huggingface.co/JY623/KoSOLAR-v2.0) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 5.1419
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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|
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## Training procedure
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|
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 7
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 28
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- total_eval_batch_size: 7
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 20
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- num_epochs: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 13.4775 | 0.0 | 1 | 13.4330 |
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| 6.9219 | 0.25 | 64 | 6.2022 |
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| 5.5416 | 0.5 | 128 | 5.2780 |
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| 5.4282 | 0.75 | 192 | 5.1929 |
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| 5.4864 | 1.0 | 256 | 5.1416 |
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| 5.2877 | 1.24 | 320 | 5.1441 |
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| 5.1731 | 1.49 | 384 | 5.1413 |
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| 5.6221 | 1.74 | 448 | 5.1406 |
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| 5.3737 | 1.99 | 512 | 5.1419 |
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+
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+
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### Framework versions
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- PEFT 0.9.0
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- Transformers 4.40.0.dev0
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.0
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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": "JY623/KoSOLAR-v2.0",
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"bias": "none",
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"fan_in_fan_out": null,
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"inference_mode": true,
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"init_lora_weights": true,
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9 |
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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": 16,
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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": 32,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"up_proj",
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"k_proj",
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"gate_proj",
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"q_proj",
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"o_proj",
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"v_proj",
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"down_proj"
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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.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:cd8ffd79d6f9619469f3bfb984a5365af2b06f81f2df30508fdf665cd7e2c811
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size 503559370
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checkpoint-256/README.md
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---
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library_name: peft
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base_model: JY623/KoSOLAR-v2.0
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---
|
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|
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# Model Card for Model ID
|
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|
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+
<!-- Provide a quick summary of what the model is/does. -->
|
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|
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|
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|
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## Model Details
|
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|
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### Model Description
|
15 |
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|
16 |
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<!-- Provide a longer summary of what this model is. -->
|
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|
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|
19 |
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|
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- **Developed by:** [More Information Needed]
|
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- **Funded by [optional]:** [More Information Needed]
|
22 |
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- **Shared by [optional]:** [More Information Needed]
|
23 |
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- **Model type:** [More Information Needed]
|
24 |
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- **Language(s) (NLP):** [More Information Needed]
|
25 |
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- **License:** [More Information Needed]
|
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- **Finetuned from model [optional]:** [More Information Needed]
|
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|
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### Model Sources [optional]
|
29 |
+
|
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<!-- Provide the basic links for the model. -->
|
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|
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- **Repository:** [More Information Needed]
|
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- **Paper [optional]:** [More Information Needed]
|
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- **Demo [optional]:** [More Information Needed]
|
35 |
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|
36 |
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## Uses
|
37 |
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|
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
39 |
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|
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### Direct Use
|
41 |
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|
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
43 |
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|
44 |
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[More Information Needed]
|
45 |
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|
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### Downstream Use [optional]
|
47 |
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|
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
49 |
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|
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[More Information Needed]
|
51 |
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|
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### Out-of-Scope Use
|
53 |
+
|
54 |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
55 |
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|
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[More Information Needed]
|
57 |
+
|
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## Bias, Risks, and Limitations
|
59 |
+
|
60 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
61 |
+
|
62 |
+
[More Information Needed]
|
63 |
+
|
64 |
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### Recommendations
|
65 |
+
|
66 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
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+
|
68 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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|
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## How to Get Started with the Model
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71 |
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|
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Use the code below to get started with the model.
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73 |
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|
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[More Information Needed]
|
75 |
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|
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## Training Details
|
77 |
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|
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### Training Data
|
79 |
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80 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
81 |
+
|
82 |
+
[More Information Needed]
|
83 |
+
|
84 |
+
### Training Procedure
|
85 |
+
|
86 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
87 |
+
|
88 |
+
#### Preprocessing [optional]
|
89 |
+
|
90 |
+
[More Information Needed]
|
91 |
+
|
92 |
+
|
93 |
+
#### Training Hyperparameters
|
94 |
+
|
95 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
96 |
+
|
97 |
+
#### Speeds, Sizes, Times [optional]
|
98 |
+
|
99 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
100 |
+
|
101 |
+
[More Information Needed]
|
102 |
+
|
103 |
+
## Evaluation
|
104 |
+
|
105 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
106 |
+
|
107 |
+
### Testing Data, Factors & Metrics
|
108 |
+
|
109 |
+
#### Testing Data
|
110 |
+
|
111 |
+
<!-- This should link to a Dataset Card if possible. -->
|
112 |
+
|
113 |
+
[More Information Needed]
|
114 |
+
|
115 |
+
#### Factors
|
116 |
+
|
117 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
118 |
+
|
119 |
+
[More Information Needed]
|
120 |
+
|
121 |
+
#### Metrics
|
122 |
+
|
123 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
124 |
+
|
125 |
+
[More Information Needed]
|
126 |
+
|
127 |
+
### Results
|
128 |
+
|
129 |
+
[More Information Needed]
|
130 |
+
|
131 |
+
#### Summary
|
132 |
+
|
133 |
+
|
134 |
+
|
135 |
+
## Model Examination [optional]
|
136 |
+
|
137 |
+
<!-- Relevant interpretability work for the model goes here -->
|
138 |
+
|
139 |
+
[More Information Needed]
|
140 |
+
|
141 |
+
## Environmental Impact
|
142 |
+
|
143 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
144 |
+
|
145 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
146 |
+
|
147 |
+
- **Hardware Type:** [More Information Needed]
|
148 |
+
- **Hours used:** [More Information Needed]
|
149 |
+
- **Cloud Provider:** [More Information Needed]
|
150 |
+
- **Compute Region:** [More Information Needed]
|
151 |
+
- **Carbon Emitted:** [More Information Needed]
|
152 |
+
|
153 |
+
## Technical Specifications [optional]
|
154 |
+
|
155 |
+
### Model Architecture and Objective
|
156 |
+
|
157 |
+
[More Information Needed]
|
158 |
+
|
159 |
+
### Compute Infrastructure
|
160 |
+
|
161 |
+
[More Information Needed]
|
162 |
+
|
163 |
+
#### Hardware
|
164 |
+
|
165 |
+
[More Information Needed]
|
166 |
+
|
167 |
+
#### Software
|
168 |
+
|
169 |
+
[More Information Needed]
|
170 |
+
|
171 |
+
## Citation [optional]
|
172 |
+
|
173 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
174 |
+
|
175 |
+
**BibTeX:**
|
176 |
+
|
177 |
+
[More Information Needed]
|
178 |
+
|
179 |
+
**APA:**
|
180 |
+
|
181 |
+
[More Information Needed]
|
182 |
+
|
183 |
+
## Glossary [optional]
|
184 |
+
|
185 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
186 |
+
|
187 |
+
[More Information Needed]
|
188 |
+
|
189 |
+
## More Information [optional]
|
190 |
+
|
191 |
+
[More Information Needed]
|
192 |
+
|
193 |
+
## Model Card Authors [optional]
|
194 |
+
|
195 |
+
[More Information Needed]
|
196 |
+
|
197 |
+
## Model Card Contact
|
198 |
+
|
199 |
+
[More Information Needed]
|
200 |
+
### Framework versions
|
201 |
+
|
202 |
+
- PEFT 0.9.0
|
checkpoint-256/adapter_config.json
ADDED
@@ -0,0 +1,33 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
1 |
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|
2 |
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|
3 |
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|
4 |
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|
5 |
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|
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|
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|
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|
9 |
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|
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|
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|
12 |
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|
13 |
+
"lora_dropout": 0.05,
|
14 |
+
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|
15 |
+
"megatron_core": "megatron.core",
|
16 |
+
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|
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+
"peft_type": "LORA",
|
18 |
+
"r": 32,
|
19 |
+
"rank_pattern": {},
|
20 |
+
"revision": null,
|
21 |
+
"target_modules": [
|
22 |
+
"up_proj",
|
23 |
+
"k_proj",
|
24 |
+
"gate_proj",
|
25 |
+
"q_proj",
|
26 |
+
"o_proj",
|
27 |
+
"v_proj",
|
28 |
+
"down_proj"
|
29 |
+
],
|
30 |
+
"task_type": "CAUSAL_LM",
|
31 |
+
"use_dora": false,
|
32 |
+
"use_rslora": false
|
33 |
+
}
|
checkpoint-256/adapter_model.safetensors
ADDED
@@ -0,0 +1,3 @@
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|
checkpoint-256/optimizer.pt
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checkpoint-256/rng_state_0.pth
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checkpoint-256/rng_state_1.pth
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checkpoint-256/rng_state_2.pth
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checkpoint-256/rng_state_3.pth
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checkpoint-256/rng_state_4.pth
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checkpoint-256/rng_state_5.pth
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checkpoint-256/rng_state_6.pth
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checkpoint-256/scheduler.pt
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|
checkpoint-256/special_tokens_map.json
ADDED
@@ -0,0 +1,30 @@
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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},
|
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|
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"content": "</s>",
|
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|
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|
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|
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|
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+
},
|
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+
"unk_token": {
|
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+
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|
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+
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|
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+
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|
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+
"rstrip": false,
|
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+
"single_word": false
|
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+
}
|
30 |
+
}
|
checkpoint-256/tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|
checkpoint-256/tokenizer_config.json
ADDED
@@ -0,0 +1,45 @@
|
|
|
|
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|
|
|
|
|
|
|
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{
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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+
},
|
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|
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|
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|
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|
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|
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|
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|
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+
},
|
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|
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|
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|
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|
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|
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|
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+
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|
28 |
+
}
|
29 |
+
},
|
30 |
+
"additional_special_tokens": [],
|
31 |
+
"bos_token": "<s>",
|
32 |
+
"chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{% if message['content']%}{{'### System:\n' + message['content']+'\n\n'}}{% endif %}{% elif message['role'] == 'user' %}{{'### User:\n' + message['content']+'\n\n'}}{% elif message['role'] == 'assistant' %}{{'### Assistant:\n' + message['content']}}{% endif %}{% if loop.last and add_generation_prompt %}{{ '### Assistant:\n' }}{% endif %}{% endfor %}",
|
33 |
+
"clean_up_tokenization_spaces": false,
|
34 |
+
"eos_token": "</s>",
|
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+
"legacy": true,
|
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+
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|
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+
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|
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+
"padding_side": "left",
|
39 |
+
"sp_model_kwargs": {},
|
40 |
+
"spaces_between_special_tokens": false,
|
41 |
+
"split_special_tokens": false,
|
42 |
+
"tokenizer_class": "LlamaTokenizer",
|
43 |
+
"unk_token": "<unk>",
|
44 |
+
"use_default_system_prompt": true
|
45 |
+
}
|
checkpoint-256/trainer_state.json
ADDED
@@ -0,0 +1,1853 @@
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size 5624
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checkpoint-512/README.md
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1 |
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---
|
2 |
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library_name: peft
|
3 |
+
base_model: JY623/KoSOLAR-v2.0
|
4 |
+
---
|
5 |
+
|
6 |
+
# Model Card for Model ID
|
7 |
+
|
8 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
9 |
+
|
10 |
+
|
11 |
+
|
12 |
+
## Model Details
|
13 |
+
|
14 |
+
### Model Description
|
15 |
+
|
16 |
+
<!-- Provide a longer summary of what this model is. -->
|
17 |
+
|
18 |
+
|
19 |
+
|
20 |
+
- **Developed by:** [More Information Needed]
|
21 |
+
- **Funded by [optional]:** [More Information Needed]
|
22 |
+
- **Shared by [optional]:** [More Information Needed]
|
23 |
+
- **Model type:** [More Information Needed]
|
24 |
+
- **Language(s) (NLP):** [More Information Needed]
|
25 |
+
- **License:** [More Information Needed]
|
26 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
27 |
+
|
28 |
+
### Model Sources [optional]
|
29 |
+
|
30 |
+
<!-- Provide the basic links for the model. -->
|
31 |
+
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32 |
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- **Repository:** [More Information Needed]
|
33 |
+
- **Paper [optional]:** [More Information Needed]
|
34 |
+
- **Demo [optional]:** [More Information Needed]
|
35 |
+
|
36 |
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## Uses
|
37 |
+
|
38 |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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39 |
+
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40 |
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### Direct Use
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41 |
+
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42 |
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
43 |
+
|
44 |
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[More Information Needed]
|
45 |
+
|
46 |
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### Downstream Use [optional]
|
47 |
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48 |
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
49 |
+
|
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[More Information Needed]
|
51 |
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|
52 |
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### Out-of-Scope Use
|
53 |
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|
54 |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
55 |
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56 |
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[More Information Needed]
|
57 |
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|
58 |
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## Bias, Risks, and Limitations
|
59 |
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|
60 |
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
61 |
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|
62 |
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[More Information Needed]
|
63 |
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|
64 |
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### Recommendations
|
65 |
+
|
66 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
67 |
+
|
68 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
69 |
+
|
70 |
+
## How to Get Started with the Model
|
71 |
+
|
72 |
+
Use the code below to get started with the model.
|
73 |
+
|
74 |
+
[More Information Needed]
|
75 |
+
|
76 |
+
## Training Details
|
77 |
+
|
78 |
+
### Training Data
|
79 |
+
|
80 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
81 |
+
|
82 |
+
[More Information Needed]
|
83 |
+
|
84 |
+
### Training Procedure
|
85 |
+
|
86 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
87 |
+
|
88 |
+
#### Preprocessing [optional]
|
89 |
+
|
90 |
+
[More Information Needed]
|
91 |
+
|
92 |
+
|
93 |
+
#### Training Hyperparameters
|
94 |
+
|
95 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
96 |
+
|
97 |
+
#### Speeds, Sizes, Times [optional]
|
98 |
+
|
99 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
100 |
+
|
101 |
+
[More Information Needed]
|
102 |
+
|
103 |
+
## Evaluation
|
104 |
+
|
105 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
106 |
+
|
107 |
+
### Testing Data, Factors & Metrics
|
108 |
+
|
109 |
+
#### Testing Data
|
110 |
+
|
111 |
+
<!-- This should link to a Dataset Card if possible. -->
|
112 |
+
|
113 |
+
[More Information Needed]
|
114 |
+
|
115 |
+
#### Factors
|
116 |
+
|
117 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
118 |
+
|
119 |
+
[More Information Needed]
|
120 |
+
|
121 |
+
#### Metrics
|
122 |
+
|
123 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
124 |
+
|
125 |
+
[More Information Needed]
|
126 |
+
|
127 |
+
### Results
|
128 |
+
|
129 |
+
[More Information Needed]
|
130 |
+
|
131 |
+
#### Summary
|
132 |
+
|
133 |
+
|
134 |
+
|
135 |
+
## Model Examination [optional]
|
136 |
+
|
137 |
+
<!-- Relevant interpretability work for the model goes here -->
|
138 |
+
|
139 |
+
[More Information Needed]
|
140 |
+
|
141 |
+
## Environmental Impact
|
142 |
+
|
143 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
144 |
+
|
145 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
146 |
+
|
147 |
+
- **Hardware Type:** [More Information Needed]
|
148 |
+
- **Hours used:** [More Information Needed]
|
149 |
+
- **Cloud Provider:** [More Information Needed]
|
150 |
+
- **Compute Region:** [More Information Needed]
|
151 |
+
- **Carbon Emitted:** [More Information Needed]
|
152 |
+
|
153 |
+
## Technical Specifications [optional]
|
154 |
+
|
155 |
+
### Model Architecture and Objective
|
156 |
+
|
157 |
+
[More Information Needed]
|
158 |
+
|
159 |
+
### Compute Infrastructure
|
160 |
+
|
161 |
+
[More Information Needed]
|
162 |
+
|
163 |
+
#### Hardware
|
164 |
+
|
165 |
+
[More Information Needed]
|
166 |
+
|
167 |
+
#### Software
|
168 |
+
|
169 |
+
[More Information Needed]
|
170 |
+
|
171 |
+
## Citation [optional]
|
172 |
+
|
173 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
174 |
+
|
175 |
+
**BibTeX:**
|
176 |
+
|
177 |
+
[More Information Needed]
|
178 |
+
|
179 |
+
**APA:**
|
180 |
+
|
181 |
+
[More Information Needed]
|
182 |
+
|
183 |
+
## Glossary [optional]
|
184 |
+
|
185 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
186 |
+
|
187 |
+
[More Information Needed]
|
188 |
+
|
189 |
+
## More Information [optional]
|
190 |
+
|
191 |
+
[More Information Needed]
|
192 |
+
|
193 |
+
## Model Card Authors [optional]
|
194 |
+
|
195 |
+
[More Information Needed]
|
196 |
+
|
197 |
+
## Model Card Contact
|
198 |
+
|
199 |
+
[More Information Needed]
|
200 |
+
### Framework versions
|
201 |
+
|
202 |
+
- PEFT 0.9.0
|
checkpoint-512/adapter_config.json
ADDED
@@ -0,0 +1,33 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
|
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|
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|
|
|
|
|
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|
|
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|
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|
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|
|
1 |
+
{
|
2 |
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"alpha_pattern": {},
|
3 |
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"auto_mapping": null,
|
4 |
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"base_model_name_or_path": "JY623/KoSOLAR-v2.0",
|
5 |
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"bias": "none",
|
6 |
+
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|
7 |
+
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|
8 |
+
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|
9 |
+
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|
10 |
+
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|
11 |
+
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|
12 |
+
"lora_alpha": 16,
|
13 |
+
"lora_dropout": 0.05,
|
14 |
+
"megatron_config": null,
|
15 |
+
"megatron_core": "megatron.core",
|
16 |
+
"modules_to_save": null,
|
17 |
+
"peft_type": "LORA",
|
18 |
+
"r": 32,
|
19 |
+
"rank_pattern": {},
|
20 |
+
"revision": null,
|
21 |
+
"target_modules": [
|
22 |
+
"up_proj",
|
23 |
+
"k_proj",
|
24 |
+
"gate_proj",
|
25 |
+
"q_proj",
|
26 |
+
"o_proj",
|
27 |
+
"v_proj",
|
28 |
+
"down_proj"
|
29 |
+
],
|
30 |
+
"task_type": "CAUSAL_LM",
|
31 |
+
"use_dora": false,
|
32 |
+
"use_rslora": false
|
33 |
+
}
|
checkpoint-512/adapter_model.safetensors
ADDED
@@ -0,0 +1,3 @@
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|
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|
checkpoint-512/optimizer.pt
ADDED
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checkpoint-512/rng_state_1.pth
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|
checkpoint-512/rng_state_2.pth
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checkpoint-512/rng_state_3.pth
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checkpoint-512/rng_state_4.pth
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checkpoint-512/rng_state_5.pth
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checkpoint-512/rng_state_6.pth
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checkpoint-512/scheduler.pt
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|
checkpoint-512/special_tokens_map.json
ADDED
@@ -0,0 +1,30 @@
|
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|
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|
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|
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|
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|
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|
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|
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},
|
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|
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|
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|
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|
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|
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|
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},
|
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|
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"content": "</s>",
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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+
"rstrip": false,
|
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+
"single_word": false
|
29 |
+
}
|
30 |
+
}
|
checkpoint-512/tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|
checkpoint-512/tokenizer_config.json
ADDED
@@ -0,0 +1,45 @@
|
|
|
|
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|
|
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|
|
|
|
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|
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{
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
12 |
+
},
|
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|
14 |
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|
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|
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|
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|
18 |
+
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|
19 |
+
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|
20 |
+
},
|
21 |
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|
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|
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|
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|
25 |
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|
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|
27 |
+
"special": true
|
28 |
+
}
|
29 |
+
},
|
30 |
+
"additional_special_tokens": [],
|
31 |
+
"bos_token": "<s>",
|
32 |
+
"chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{% if message['content']%}{{'### System:\n' + message['content']+'\n\n'}}{% endif %}{% elif message['role'] == 'user' %}{{'### User:\n' + message['content']+'\n\n'}}{% elif message['role'] == 'assistant' %}{{'### Assistant:\n' + message['content']}}{% endif %}{% if loop.last and add_generation_prompt %}{{ '### Assistant:\n' }}{% endif %}{% endfor %}",
|
33 |
+
"clean_up_tokenization_spaces": false,
|
34 |
+
"eos_token": "</s>",
|
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+
"legacy": true,
|
36 |
+
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|
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+
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|
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+
"padding_side": "left",
|
39 |
+
"sp_model_kwargs": {},
|
40 |
+
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|
41 |
+
"split_special_tokens": false,
|
42 |
+
"tokenizer_class": "LlamaTokenizer",
|
43 |
+
"unk_token": "<unk>",
|
44 |
+
"use_default_system_prompt": true
|
45 |
+
}
|
checkpoint-512/trainer_state.json
ADDED
@@ -0,0 +1,3677 @@
|
|
|
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|
|
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|
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|
|
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1 |
+
{
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2 |
+
"add_bos_token": true,
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3 |
+
"add_eos_token": false,
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4 |
+
"added_tokens_decoder": {
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5 |
+
"0": {
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6 |
+
"content": "<unk>",
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7 |
+
"lstrip": false,
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8 |
+
"normalized": false,
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9 |
+
"rstrip": false,
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10 |
+
"single_word": false,
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11 |
+
"special": true
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12 |
+
},
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13 |
+
"1": {
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14 |
+
"content": "<s>",
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15 |
+
"lstrip": false,
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16 |
+
"normalized": false,
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17 |
+
"rstrip": false,
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18 |
+
"single_word": false,
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19 |
+
"special": true
|
20 |
+
},
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21 |
+
"2": {
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22 |
+
"content": "</s>",
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23 |
+
"lstrip": false,
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24 |
+
"normalized": false,
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25 |
+
"rstrip": false,
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26 |
+
"single_word": false,
|
27 |
+
"special": true
|
28 |
+
}
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29 |
+
},
|
30 |
+
"additional_special_tokens": [],
|
31 |
+
"bos_token": "<s>",
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32 |
+
"chat_template": "{% for message in messages %}{% if message['role'] == 'system' %}{% if message['content']%}{{'### System:\n' + message['content']+'\n\n'}}{% endif %}{% elif message['role'] == 'user' %}{{'### User:\n' + message['content']+'\n\n'}}{% elif message['role'] == 'assistant' %}{{'### Assistant:\n' + message['content']}}{% endif %}{% if loop.last and add_generation_prompt %}{{ '### Assistant:\n' }}{% endif %}{% endfor %}",
|
33 |
+
"clean_up_tokenization_spaces": false,
|
34 |
+
"eos_token": "</s>",
|
35 |
+
"legacy": true,
|
36 |
+
"model_max_length": 1000000000000000019884624838656,
|
37 |
+
"pad_token": "</s>",
|
38 |
+
"padding_side": "left",
|
39 |
+
"sp_model_kwargs": {},
|
40 |
+
"spaces_between_special_tokens": false,
|
41 |
+
"split_special_tokens": false,
|
42 |
+
"tokenizer_class": "LlamaTokenizer",
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43 |
+
"unk_token": "<unk>",
|
44 |
+
"use_default_system_prompt": true
|
45 |
+
}
|