elichen3051
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Model save
Browse files- README.md +160 -0
- generation_config.json +7 -0
README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: skymizer/mistral-7B-v0.1-sft-slim-orca-sonnet-3.5-v4
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tags:
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- axolotl
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- generated_from_trainer
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model-index:
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- name: mistral-7B-v0.1-csft-relu2-on-slim-orca
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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: `0.5.2`
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```yaml
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base_model: skymizer/mistral-7B-v0.1-sft-slim-orca-sonnet-3.5-v4
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model_type: AutoModelForCausalLM
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tokenizer_type: AutoTokenizer
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tokenizer_use_fast: false
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resize_token_embeddings_to_32x: false
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flash_attention: true
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xformers_attention:
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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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chat_template: chatml
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datasets:
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- path: skymizer/Sonnet3.5-SlimOrcaDedupCleaned
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type: chat_template
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field_messages: messages
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test_datasets:
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- path: skymizer/Sonnet3.5-SlimOrcaDedupCleaned
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type: chat_template
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field_messages: messages
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split: test
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hf_use_auth_token: true
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dataset_prepared_path: pretokenized/slim-orca
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output_dir: ./exp_output_artifacts
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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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eval_sample_packing: false
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# eval_causal_lm_metrics: ["perplexity"]
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wandb_project: "axolotl_mistral_sft"
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wandb_entity:
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wandb_watch:
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wandb_name: "mistral-7B-v0.1-csft-relu2-on-slim-orca"
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wandb_log_model:
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gradient_accumulation_steps: 2
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micro_batch_size: 16
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eval_batch_size: 1
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num_epochs: 1
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optimizer: adamw_torch
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lr_scheduler: cosine
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learning_rate: 0.000005
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weight_decay: 0.0
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adam_beta1: 0.9
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adam_beta2: 0.95
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adam_eps: 0.000001
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max_grad_norm: 1.0
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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:
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tf32: false
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hub_model_id: "skymizer/mistral-7B-v0.1-csft-relu2-on-slim-orca"
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save_strategy: "steps"
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save_steps: 50
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gradient_checkpointing: true
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gradient_checkpointing_kwargs:
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use_reentrant: false
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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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warmup_ratio: 0.03
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eval_steps: 50
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eval_table_size:
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eval_max_new_tokens: 2048
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debug:
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deepspeed: deepspeed_configs/zero3_bf16.json
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fsdp:
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fsdp_config:
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seed: 42
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```
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</details><br>
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# mistral-7B-v0.1-csft-relu2-on-slim-orca
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This model is a fine-tuned version of [skymizer/mistral-7B-v0.1-sft-slim-orca-sonnet-3.5-v4](https://huggingface.co/skymizer/mistral-7B-v0.1-sft-slim-orca-sonnet-3.5-v4) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 5.6672
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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-06
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- train_batch_size: 16
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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: 8
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 256
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- total_eval_batch_size: 8
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.95) 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: 5
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 15.3694 | 0.0051 | 1 | 14.8551 |
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| 6.8825 | 0.2558 | 50 | 6.7523 |
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| 6.1034 | 0.5115 | 100 | 6.0549 |
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| 5.7432 | 0.7673 | 150 | 5.6672 |
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### Framework versions
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- Transformers 4.46.3
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- Pytorch 2.5.1+cu124
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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generation_config.json
ADDED
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"do_sample": true,
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"eos_token_id": 32000,
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"transformers_version": "4.46.3"
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}
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