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manu
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croissant_mmlu

Text Generation
Transformers
PyTorch
TensorBoard
Safetensors
llama
Generated from Trainer
text-generation-inference
Inference Endpoints
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  1. README.md +148 -0
  2. checkpoint-275/config.json +28 -0
  3. checkpoint-275/generation_config.json +7 -0
  4. checkpoint-275/model.safetensors +3 -0
  5. checkpoint-275/optimizer.pt +3 -0
  6. checkpoint-275/rng_state.pth +3 -0
  7. checkpoint-275/scheduler.pt +3 -0
  8. checkpoint-275/trainer_state.json +1703 -0
  9. checkpoint-275/training_args.bin +3 -0
  10. checkpoint-550/config.json +28 -0
  11. checkpoint-550/generation_config.json +7 -0
  12. checkpoint-550/model.safetensors +3 -0
  13. checkpoint-550/optimizer.pt +3 -0
  14. checkpoint-550/rng_state.pth +3 -0
  15. checkpoint-550/scheduler.pt +3 -0
  16. checkpoint-550/trainer_state.json +3385 -0
  17. checkpoint-550/training_args.bin +3 -0
  18. config.json +28 -0
  19. generation_config.json +7 -0
  20. pytorch_model.bin +3 -0
  21. runs/Feb08_14-38-32_ruche-gpu12.cluster/events.out.tfevents.1707399515.ruche-gpu12.cluster.26480.0 +3 -0
  22. runs/Feb08_14-45-27_ruche-gpu12.cluster/events.out.tfevents.1707399931.ruche-gpu12.cluster.27626.0 +3 -0
  23. runs/Feb08_15-00-36_ruche-gpu12.cluster/events.out.tfevents.1707400839.ruche-gpu12.cluster.29774.0 +3 -0
  24. runs/Feb08_15-17-32_ruche-gpu12.cluster/events.out.tfevents.1707401856.ruche-gpu12.cluster.664.0 +3 -0
  25. special_tokens_map.json +24 -0
  26. tokenizer.json +0 -0
  27. tokenizer_config.json +849 -0
README.md ADDED
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+ ---
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+ license: mit
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+ base_model: croissantllm/CroissantLLMBase
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: out
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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: croissantllm/CroissantLLMBase
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+ model_type: LlamaForCausalLM
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+ tokenizer_type: LlamaTokenizerFast
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+ is_llama_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: manu/mmlu_auxiliary_train_formatted_2
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+ split: train
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+ type: completion
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+
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+ dataset_prepared_path: last_run_prepared
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+ val_set_size: 0.05
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+ output_dir: ./out
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+
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+ sequence_len: 2048
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+ sample_packing: true
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+ pad_to_sequence_len: true
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+
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+ adapter:
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+ lora_model_dir:
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+ lora_r:
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+ lora_alpha:
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+ lora_dropout:
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+ lora_target_linear:
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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: 16
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+ num_epochs: 2
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+ optimizer: adamw_bnb_8bit
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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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+
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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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+ flash_attn_cross_entropy: false
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+ flash_attn_rms_norm: true
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+ flash_attn_fuse_qkv: false
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+ flash_attn_fuse_mlp: true
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+
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+ warmup_steps: 50
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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: #deepspeed_configs/zero2.json # multi-gpu only
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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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+
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+ ```
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+
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+ </details><br>
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+
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+ # out
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+
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+ This model is a fine-tuned version of [croissantllm/CroissantLLMBase](https://huggingface.co/croissantllm/CroissantLLMBase) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7378
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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
108
+
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+ ## Training and evaluation data
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+
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+ More information needed
112
+
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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: 0.0002
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 64
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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: 50
127
+ - num_epochs: 2
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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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+ |:-------------:|:-----:|:----:|:---------------:|
133
+ | 2.5429 | 0.0 | 1 | 2.5242 |
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+ | 2.2283 | 0.25 | 69 | 2.2514 |
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+ | 1.9539 | 0.5 | 138 | 2.0381 |
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+ | 1.6608 | 0.75 | 207 | 1.6872 |
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+ | 1.3767 | 1.0 | 276 | 1.3323 |
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+ | 0.7872 | 1.23 | 345 | 1.0583 |
139
+ | 0.5873 | 1.48 | 414 | 0.8251 |
140
+ | 0.5154 | 1.73 | 483 | 0.7378 |
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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
146
+ - Pytorch 2.1.2+cu121
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+ - Datasets 2.16.1
148
+ - Tokenizers 0.15.0
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