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README.md CHANGED
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  ---
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- license: mit
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: workspace/output/cosmosage_qa
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+ results: []
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  ---
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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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+
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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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+
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+ axolotl version: `0.4.0`
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+ ```yaml
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+ base_model: /workspace/output/cosmosage_base/
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+ model_type: MistralForCausalLM
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+ tokenizer_type: LlamaTokenizer
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+ is_mistral_derived_model: true
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+
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+ load_in_8bit: false
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+ load_in_4bit: false
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+ strict: false
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+
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+ datasets:
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+ - path: /workspace/input/datasets/qa_tune/arxiv_metadata_qa3.jsonl
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+ type: sharegpt
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+ - path: /workspace/input/datasets/qa_tune/arxiv_refined_qa.jsonl
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+ type: sharegpt
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+ - path: /workspace/input/datasets/qa_tune/arxiv_summary3.jsonl
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+ type: sharegpt
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+ - path: /workspace/input/datasets/qa_tune/cosmology_qa.jsonl
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+ type: alpaca_chat.load_qa
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+ - path: /workspace/input/datasets/qa_tune/openhermes2_5.jsonl
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+ type: sharegpt
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+ - path: /workspace/input/datasets/qa_tune/cosmology_textbooks_qa.jsonl
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+ type: alpaca_chat.load_qa
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+ - path: /workspace/input/datasets/qa_tune/physics_astro_qa.jsonl
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+ type: alpaca_chat.load_qa
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+
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+ dataset_prepared_path: /workspace/output/qa_tune_prepared
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+ val_set_size: 0.001
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+ output_dir: /workspace/output/cosmosage_qa
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+
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+ chat_template: inst
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+
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+ adapter:
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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:
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+ lora_alpha:
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+ lora_dropout:
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+ lora_target_modules:
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+ lora_target_linear:
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+ lora_fan_in_fan_out:
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+
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+ seed: 702
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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: 1
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+ micro_batch_size: 4
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+ num_epochs: 2.0
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+ optimizer: adamw_torch
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+ lr_scheduler: linear
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+ learning_rate: 0.000002
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+ max_grad_norm: 3.0
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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: true
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+ fp16: false
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+ tf32: false
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+
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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: true
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+
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+ warmup_steps: 100
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+ eval_steps: 0.05
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+ eval_table_size:
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+ eval_table_max_new_tokens: 128
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+ saves_per_epoch: 1
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+ save_total_limit: 2
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+ debug:
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+ deepspeed: /workspace/axolotl/deepspeed_configs/zero1.json
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+ weight_decay:
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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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+ ddp_timeout: 7200000
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+
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+ ```
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+
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+ </details><br>
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+
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+ # workspace/output/cosmosage_qa
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+
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+ This model was trained from scratch on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5673
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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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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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-06
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 702
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+ - distributed_type: multi-GPU
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+ - num_devices: 4
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+ - total_train_batch_size: 16
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+ - total_eval_batch_size: 16
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 2.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:---------------:|
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+ | 1.1004 | 0.0 | 1 | 1.1450 |
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+ | 0.7343 | 0.1 | 909 | 0.7093 |
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+ | 0.697 | 0.2 | 1818 | 0.6630 |
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+ | 0.6386 | 0.3 | 2727 | 0.6380 |
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+ | 0.5687 | 0.4 | 3636 | 0.6212 |
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+ | 0.5857 | 0.5 | 4545 | 0.6083 |
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+ | 0.6161 | 0.6 | 5454 | 0.5986 |
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+ | 0.522 | 0.7 | 6363 | 0.5894 |
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+ | 0.5563 | 0.8 | 7272 | 0.5825 |
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+ | 0.6176 | 0.9 | 8181 | 0.5766 |
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+ | 0.5948 | 1.0 | 9090 | 0.5719 |
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+ | 0.4269 | 1.08 | 9999 | 0.5817 |
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+ | 0.4858 | 1.18 | 10908 | 0.5796 |
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+ | 0.4909 | 1.28 | 11817 | 0.5765 |
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+ | 0.4325 | 1.38 | 12726 | 0.5746 |
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+ | 0.4037 | 1.48 | 13635 | 0.5720 |
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+ | 0.507 | 1.58 | 14544 | 0.5706 |
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+ | 0.4778 | 1.68 | 15453 | 0.5697 |
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+ | 0.4599 | 1.78 | 16362 | 0.5683 |
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+ | 0.4515 | 1.88 | 17271 | 0.5673 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.0.dev0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.17.0
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+ - Tokenizers 0.15.0
config.json ADDED
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+ {
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+ "_name_or_path": "/workspace/output/cosmosage_base/",
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+ "architectures": [
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+ "MistralForCausalLM"
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+ ],
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "hidden_act": "silu",
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+ "hidden_size": 4096,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 14336,
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+ "max_position_embeddings": 32768,
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+ "model_type": "mistral",
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+ "num_attention_heads": 32,
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+ "num_hidden_layers": 32,
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+ "num_key_value_heads": 8,
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+ "rms_norm_eps": 1e-05,
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+ "rope_theta": 10000.0,
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+ "sliding_window": 4096,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.38.0.dev0",
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+ "use_cache": false,
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+ "vocab_size": 32000
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+ }
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+ {
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+ "_from_model_config": true,
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+ "transformers_version": "4.38.0.dev0"
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+ }
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+ "chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}",
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