End of training
Browse files- README.md +154 -0
- pytorch_model-00001-of-00003.bin +1 -1
- pytorch_model-00002-of-00003.bin +1 -1
- pytorch_model-00003-of-00003.bin +1 -1
README.md
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---
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library_name: transformers
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base_model: jeiku/MoEv2
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tags:
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- axolotl
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- generated_from_trainer
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datasets:
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- FourOhFour/RP_Phase
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- jeiku/Writing
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model-index:
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- name: Aura-MoEv2
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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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
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<details><summary>See axolotl config</summary>
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axolotl version: `0.6.0`
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```yaml
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base_model: jeiku/MoEv2
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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: false
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strict: false
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datasets:
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- path: FourOhFour/RP_Phase
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type: chat_template
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chat_template: chatml
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roles_to_train: ["gpt"]
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field_messages: conversations
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message_field_role: from
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message_field_content: value
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train_on_eos: turn
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- path: jeiku/Writing
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type: completion
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field: text
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chat_template: chatml
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shuffle_merged_datasets: true
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dataset_prepared_path:
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val_set_size: 0.01
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output_dir: ./output/out
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hub_model_id: jeiku/Aura-MoEv2
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hub_strategy: "all_checkpoints"
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push_dataset_to_hub:
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hf_use_auth_token: true
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sequence_len: 8192
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sample_packing: true
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eval_sample_packing: false
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pad_to_sequence_len:
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wandb_project: Aura-MoEv2
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wandb_entity:
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wandb_watch:
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wandb_name: Aura-MoEv2
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wandb_log_model:
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gradient_accumulation_steps: 16
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micro_batch_size: 2
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num_epochs: 2
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optimizer: paged_adamw_8bit
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lr_scheduler: cosine
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learning_rate: 0.00005
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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: true
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warmup_steps: 10
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evals_per_epoch: 2
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eval_table_size:
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eval_max_new_tokens:
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saves_per_epoch: 1
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debug:
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deepspeed:
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weight_decay: 0.05
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fsdp:
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fsdp_config:
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special_tokens:
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pad_token: <|finetune_right_pad_id|>
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```
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</details><br>
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# Aura-MoEv2
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This model is a fine-tuned version of [jeiku/MoEv2](https://huggingface.co/jeiku/MoEv2) on the FourOhFour/RP_Phase and the jeiku/Writing datasets.
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It achieves the following results on the evaluation set:
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- Loss: 1.7106
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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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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 32
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- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 10
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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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| 29.5342 | 0.0038 | 1 | 1.8693 |
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| 27.8562 | 0.4990 | 130 | 1.7601 |
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| 26.632 | 0.9981 | 260 | 1.6990 |
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| 21.9675 | 1.4952 | 390 | 1.7117 |
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| 21.648 | 1.9942 | 520 | 1.7106 |
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### Framework versions
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- Transformers 4.47.0
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- Pytorch 2.3.1+cu121
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- Datasets 3.1.0
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- Tokenizers 0.21.0
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