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--- |
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license: apache-2.0 |
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base_model: h2oai/h2o-danube3-500m-base |
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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: clite7-500m-test-ckpts |
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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: `0.4.1` |
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```yaml |
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# Weights and Biases logging config |
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wandb_project: clite |
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wandb_entity: |
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wandb_watch: |
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wandb_name: v7 |
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wandb_log_model: |
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# Model architecture config |
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base_model: h2oai/h2o-danube3-500m-base |
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model_type: AutoModelForCausalLM |
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tokenizer_type: AutoTokenizer |
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chat_template: anthropic |
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# Hugging Face saving config |
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hub_model_id: |
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hub_strategy: |
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push_dataset_to_hub: |
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hf_use_auth_token: |
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# Model checkpointing config |
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output_dir: ./lora-out |
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resume_from_checkpoint: |
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save_steps: |
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saves_per_epoch: 5 |
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save_safetensors: true |
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save_total_limit: 2 |
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# Mixed precision training config |
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bf16: true |
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fp16: false |
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tf32: false |
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# Model loading config |
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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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# Sequence config |
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sequence_len: 8192 |
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s2_attention: false |
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sample_packing: true |
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eval_sample_packing: true |
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pad_to_sequence_len: true |
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train_on_inputs: true |
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group_by_length: false |
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# Dataset config |
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datasets: |
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- path: kalomaze/Opus_Instruct_3k |
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type: chat_template |
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val_set_size: 0.1 |
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evaluation_strategy: |
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eval_steps: |
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evals_per_epoch: 10 |
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test_datasets: |
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dataset_prepared_path: ./last-preped-dataset |
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shuffle_merged_datasets: true |
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# Training hyperparameters |
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num_epochs: 3 |
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gradient_accumulation_steps: 2 |
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micro_batch_size: 8 |
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eval_batch_size: 8 |
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warmup_steps: 10 |
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optimizer: paged_adamw_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.00004 |
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cosine_min_lr_ratio: 0.1 |
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weight_decay: 0.1 |
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max_grad_norm: 1 |
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logging_steps: 1 |
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# Model optimization |
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gradient_checkpointing: unsloth |
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xformers_attention: false |
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flash_attention: true |
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sdp_attention: false |
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unsloth_cross_entropy_loss: false |
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unsloth_lora_mlp: false |
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unsloth_lora_qkv: false |
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unsloth_lora_o: false |
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# Loss monitoring config |
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early_stopping_patience: false |
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loss_watchdog_threshold: 100.0 |
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loss_watchdog_patience: 3 |
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# Debug config |
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debug: true |
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seed: 02496 |
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# DeepSpeed and FSDP config |
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deepspeed: |
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fsdp: |
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fsdp_config: |
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# Token config |
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special_tokens: |
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tokens: # these are delimiters |
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- "<EOT>" |
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# Checkpoint backing up |
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hub_model_id: Fizzarolli/clite7-500m-test-ckpts |
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hub_strategy: all_checkpoints |
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``` |
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</details><br> |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ruthenic/clite/runs/diil6zl9) |
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# clite7-500m-test-ckpts |
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This model is a fine-tuned version of [h2oai/h2o-danube3-500m-base](https://huggingface.co/h2oai/h2o-danube3-500m-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3765 |
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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: 4e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 2496 |
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- gradient_accumulation_steps: 2 |
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- total_train_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: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.9517 | 0.0952 | 1 | 3.7616 | |
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| 2.9796 | 0.1905 | 2 | 3.6462 | |
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| 2.9632 | 0.2857 | 3 | 3.3357 | |
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| 2.6639 | 0.3810 | 4 | 3.0408 | |
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| 2.5048 | 0.4762 | 5 | 2.7322 | |
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| 2.4911 | 0.5714 | 6 | 2.5094 | |
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| 2.1291 | 0.6667 | 7 | 2.3554 | |
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| 4.8452 | 0.7619 | 8 | 1.6418 | |
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| 1.6902 | 0.8571 | 9 | 1.6067 | |
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| 1.6166 | 0.9524 | 10 | 1.5581 | |
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| 1.5985 | 1.0476 | 11 | 1.5162 | |
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| 1.5001 | 1.0476 | 12 | 1.4847 | |
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| 1.4679 | 1.1429 | 13 | 1.4601 | |
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| 1.4981 | 1.2381 | 14 | 1.4440 | |
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| 1.4864 | 1.3333 | 15 | 1.4293 | |
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| 1.4895 | 1.4286 | 16 | 1.4174 | |
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| 1.4653 | 1.5238 | 17 | 1.4061 | |
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| 1.4447 | 1.6190 | 18 | 1.3988 | |
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| 1.4492 | 1.7143 | 19 | 1.3937 | |
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| 1.4244 | 1.8095 | 20 | 1.3896 | |
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| 1.4319 | 1.9048 | 21 | 1.3858 | |
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| 1.4238 | 2.0 | 22 | 1.3830 | |
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| 1.4725 | 2.0952 | 23 | 1.3810 | |
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| 1.3862 | 2.0952 | 24 | 1.3794 | |
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| 1.3526 | 2.1905 | 25 | 1.3783 | |
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| 1.4134 | 2.2857 | 26 | 1.3776 | |
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| 1.3909 | 2.3810 | 27 | 1.3771 | |
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| 1.4016 | 2.4762 | 28 | 1.3769 | |
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| 1.3494 | 2.5714 | 29 | 1.3766 | |
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| 1.3783 | 2.6667 | 30 | 1.3765 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.1.2+cu118 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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