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upload qwen2_7b training results

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  1. competition/13_Qwen2_7b_finetuning_l40.ipynb +1 -1
  2. competition/13c_Qwen2_7b_analysis.ipynb +0 -0
  3. llama-factory/config/qwen2_7b_lora_sft_4bit.yaml +4 -5
  4. llama-factory/saves/qwen2_7b/lora/sft_4bit/README.md +66 -0
  5. llama-factory/saves/qwen2_7b/lora/sft_4bit/adapter_config.json +34 -0
  6. llama-factory/saves/qwen2_7b/lora/sft_4bit/adapter_model.safetensors +3 -0
  7. llama-factory/saves/qwen2_7b/lora/sft_4bit/added_tokens.json +5 -0
  8. llama-factory/saves/qwen2_7b/lora/sft_4bit/all_results.json +12 -0
  9. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-176/README.md +202 -0
  10. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-176/adapter_config.json +34 -0
  11. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-176/adapter_model.safetensors +3 -0
  12. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-176/added_tokens.json +5 -0
  13. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-176/merges.txt +0 -0
  14. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-176/optimizer.pt +3 -0
  15. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-176/rng_state.pth +3 -0
  16. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-176/scheduler.pt +3 -0
  17. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-176/special_tokens_map.json +20 -0
  18. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-176/tokenizer.json +0 -0
  19. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-176/tokenizer_config.json +44 -0
  20. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-176/trainer_state.json +63 -0
  21. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-176/training_args.bin +3 -0
  22. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-176/vocab.json +0 -0
  23. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-264/README.md +202 -0
  24. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-264/adapter_config.json +34 -0
  25. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-264/adapter_model.safetensors +3 -0
  26. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-264/added_tokens.json +5 -0
  27. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-264/merges.txt +0 -0
  28. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-264/optimizer.pt +3 -0
  29. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-264/rng_state.pth +3 -0
  30. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-264/scheduler.pt +3 -0
  31. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-264/special_tokens_map.json +20 -0
  32. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-264/tokenizer.json +0 -0
  33. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-264/tokenizer_config.json +44 -0
  34. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-264/trainer_state.json +78 -0
  35. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-264/training_args.bin +3 -0
  36. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-264/vocab.json +0 -0
  37. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-88/README.md +202 -0
  38. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-88/adapter_config.json +34 -0
  39. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-88/adapter_model.safetensors +3 -0
  40. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-88/added_tokens.json +5 -0
  41. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-88/merges.txt +0 -0
  42. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-88/optimizer.pt +3 -0
  43. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-88/rng_state.pth +3 -0
  44. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-88/scheduler.pt +3 -0
  45. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-88/special_tokens_map.json +20 -0
  46. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-88/tokenizer.json +0 -0
  47. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-88/tokenizer_config.json +44 -0
  48. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-88/trainer_state.json +48 -0
  49. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-88/training_args.bin +3 -0
  50. llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-88/vocab.json +0 -0
competition/13_Qwen2_7b_finetuning_l40.ipynb CHANGED
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competition/13c_Qwen2_7b_analysis.ipynb ADDED
The diff for this file is too large to render. See raw diff
 
llama-factory/config/qwen2_7b_lora_sft_4bit.yaml CHANGED
@@ -20,14 +20,13 @@ preprocessing_num_workers: 16
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  ### output
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  output_dir: saves/qwen2_7b/lora/sft_4bit
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- logging_steps: 562
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- save_steps: 562
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  plot_loss: true
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- # overwrite_output_dir: true
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  # resume_from_checkpoint: true
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  ### train
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- per_device_train_batch_size: 8
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  gradient_accumulation_steps: 8
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  learning_rate: 1.0e-4
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  num_train_epochs: 3.0
@@ -40,7 +39,7 @@ ddp_timeout: 180000000
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  val_size: 0.1
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  per_device_eval_batch_size: 1
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  eval_strategy: steps
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- eval_steps: 562
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  report_to: none
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  run_name: qwen2_7b # optional
 
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  ### output
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  output_dir: saves/qwen2_7b/lora/sft_4bit
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+ logging_steps: 88
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+ save_steps: 88
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  plot_loss: true
 
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  # resume_from_checkpoint: true
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  ### train
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+ per_device_train_batch_size: 32
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  gradient_accumulation_steps: 8
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  learning_rate: 1.0e-4
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  num_train_epochs: 3.0
 
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  val_size: 0.1
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  per_device_eval_batch_size: 1
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  eval_strategy: steps
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+ eval_steps: 88
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  report_to: none
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  run_name: qwen2_7b # optional
llama-factory/saves/qwen2_7b/lora/sft_4bit/README.md ADDED
@@ -0,0 +1,66 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: other
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+ library_name: peft
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+ tags:
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+ - llama-factory
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+ - lora
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+ - generated_from_trainer
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+ base_model: Qwen/Qwen2-7B
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+ model-index:
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+ - name: sft_4bit
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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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+ # sft_4bit
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+
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+ This model is a fine-tuned version of [Qwen/Qwen2-7B](https://huggingface.co/Qwen/Qwen2-7B) on the mgtv_train dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2352
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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: 0.0001
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+ - train_batch_size: 32
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+ - eval_batch_size: 1
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+ - seed: 42
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 256
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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_ratio: 0.1
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+ - num_epochs: 3.0
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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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+ | 0.3881 | 1.0 | 88 | 0.2319 |
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+ | 0.2126 | 2.0 | 176 | 0.2290 |
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+ | 0.1536 | 3.0 | 264 | 0.2352 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.11.1
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+ - Transformers 4.41.2
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+ - Pytorch 2.4.0
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
llama-factory/saves/qwen2_7b/lora/sft_4bit/adapter_config.json ADDED
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+ {
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+ "alpha_pattern": {},
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+ "base_model_name_or_path": "Qwen/Qwen2-7B",
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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": 16,
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+ "lora_dropout": 0.0,
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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": 8,
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+ "rank_pattern": {},
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+ "revision": null,
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+ "target_modules": [
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+ "down_proj",
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+ "gate_proj",
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+ "v_proj",
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+ "k_proj",
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+ "o_proj",
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+ "up_proj",
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+ "q_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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llama-factory/saves/qwen2_7b/lora/sft_4bit/all_results.json ADDED
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+ {
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+ "epoch": 3.0,
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+ "eval_loss": 0.23515775799751282,
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+ "eval_runtime": 517.6957,
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+ "eval_samples_per_second": 4.829,
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+ "eval_steps_per_second": 4.829,
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+ "total_flos": 1.172018041404457e+18,
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+ "train_loss": 0.2514329931952737,
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+ "train_runtime": 23293.5933,
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+ "train_samples_per_second": 2.898,
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+ "train_steps_per_second": 0.011
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+ ---
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+ library_name: peft
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+ base_model: Qwen/Qwen2-7B
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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
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+
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+ <!-- Provide a longer summary of what this model is. -->
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+
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+
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+
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+ - **Developed by:** [More Information Needed]
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+ - **Funded by [optional]:** [More Information Needed]
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+ - **Shared by [optional]:** [More Information Needed]
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+ - **Model type:** [More Information Needed]
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+ - **Language(s) (NLP):** [More Information Needed]
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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]
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+
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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]
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+
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+ ## Uses
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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. -->
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+
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+ ### Direct Use
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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. -->
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+
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+ [More Information Needed]
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+
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+ ### Downstream Use [optional]
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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 -->
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+
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+ [More Information Needed]
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+
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+ ### Out-of-Scope Use
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+
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+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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+
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+ [More Information Needed]
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+
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+ ## Bias, Risks, and Limitations
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+
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+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+
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+ [More Information Needed]
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+
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+ ### Recommendations
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+
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+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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+
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+ 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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+
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+ Use the code below to get started with the model.
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+
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+ [More Information Needed]
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+
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+ ## Training Details
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+
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+ ### Training Data
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+
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+ <!-- 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. -->
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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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+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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+
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+ #### Preprocessing [optional]
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+
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+ [More Information Needed]
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+
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+
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+ #### Training Hyperparameters
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+
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+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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+
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+ #### Speeds, Sizes, Times [optional]
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+
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+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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+
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+ [More Information Needed]
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+
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+ ## Evaluation
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+
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+ <!-- This section describes the evaluation protocols and provides the results. -->
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+
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+ ### Testing Data, Factors & Metrics
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+
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+ #### Testing Data
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+
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+ <!-- This should link to a Dataset Card if possible. -->
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+
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+ [More Information Needed]
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+
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+ #### Factors
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+
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+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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+
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+ [More Information Needed]
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+
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+ #### Metrics
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+
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+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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+
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+ [More Information Needed]
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+
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+ ### Results
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+
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+ [More Information Needed]
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+
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+ #### Summary
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+
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+
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+
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+ ## Model Examination [optional]
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+
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+ <!-- Relevant interpretability work for the model goes here -->
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+
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+ [More Information Needed]
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+
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+ ## Environmental Impact
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+
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+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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+
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+ 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).
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+
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+ - **Hardware Type:** [More Information Needed]
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+ - **Hours used:** [More Information Needed]
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+ - **Cloud Provider:** [More Information Needed]
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+ - **Compute Region:** [More Information Needed]
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+ - **Carbon Emitted:** [More Information Needed]
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+
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+ ## Technical Specifications [optional]
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+
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+ ### Model Architecture and Objective
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+
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+ [More Information Needed]
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+
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+ ### Compute Infrastructure
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+
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+ [More Information Needed]
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+
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+ #### Hardware
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+
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+ [More Information Needed]
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+
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+ #### Software
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+
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+ [More Information Needed]
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+
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+ ## Citation [optional]
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+
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+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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+
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+ **BibTeX:**
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+
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+ [More Information Needed]
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+
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+ **APA:**
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+
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+ [More Information Needed]
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+
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+ ## Glossary [optional]
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+
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+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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+
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+ [More Information Needed]
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+
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+ ## More Information [optional]
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+
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+ [More Information Needed]
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+
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+ ## Model Card Authors [optional]
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+
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+ [More Information Needed]
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+
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+ ## Model Card Contact
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+
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+ [More Information Needed]
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+ ### Framework versions
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+
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+ - PEFT 0.11.1
llama-factory/saves/qwen2_7b/lora/sft_4bit/checkpoint-176/adapter_config.json ADDED
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+ "up_proj",
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+ "use_dora": false,
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+ "use_rslora": false
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+ ---
2
+ library_name: peft
3
+ base_model: Qwen/Qwen2-7B
4
+ ---
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+
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+ # Model Card for Model ID
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+ <!-- Provide a quick summary of what the model is/does. -->
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+ ## Model Details
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+ [More Information Needed]
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+ 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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+ ## How to Get Started with the Model
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+ Use the code below to get started with the model.
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+ ## Training Details
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+ ### Training Procedure
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+
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+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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+
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+ #### Preprocessing [optional]
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+ [More Information Needed]
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+ #### Training Hyperparameters
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+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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+ 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).
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+ ## Technical Specifications [optional]
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+ ### Compute Infrastructure
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+ ## Model Card Contact
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+ [More Information Needed]
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+ ### Framework versions
201
+
202
+ - PEFT 0.11.1
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+ ---
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+ library_name: peft
3
+ base_model: Qwen/Qwen2-7B
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+ ---
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+
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+ # Model Card for Model ID
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+ ## Model Details
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+ 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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+ ## How to Get Started with the Model
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+ Use the code below to get started with the model.
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+ ## Training Details
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+ ### Training Data
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+ 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).
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+ ### Framework versions
201
+
202
+ - PEFT 0.11.1
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