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--- |
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license: apache-2.0 |
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base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: tinyllama-out |
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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/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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axolotl version: `0.3.0` |
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```yaml |
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base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 |
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model_type: LlamaForCausalLM |
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tokenizer_type: LlamaTokenizer |
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is_llama_derived_model: true |
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eval_sample_packing: False #Poco dato |
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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: data.json # or json |
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ds_type: json # see other options below |
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type: completion |
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dataset_prepared_path: |
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val_set_size: 0.05 |
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# output_dir: ./lora-out |
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sequence_len: 4096 |
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sample_packing: true |
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pad_to_sequence_len: true |
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# adapter: lora |
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# lora_model_dir: |
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# lora_r: 32 |
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# lora_alpha: 16 |
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# lora_dropout: 0.05 |
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# lora_target_linear: true |
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# lora_fan_in_fan_out: |
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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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output_dir: ./tinyllama-out |
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gradient_accumulation_steps: 4 |
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micro_batch_size: 2 |
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num_epochs: 8 #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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train_on_inputs: false |
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group_by_length: false |
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bf16: true |
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fp16: false #TODO: change to true |
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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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save_strategy: "no" |
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warmup_steps: 10 |
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evals_per_epoch: 4 |
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# saves_per_epoch: 1 |
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debug: |
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deepspeed: |
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weight_decay: 0.0 |
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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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</details><br> |
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# tinyllama-out |
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This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co./TinyLlama/TinyLlama-1.1B-Chat-v1.0) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8806 |
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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: 0.0002 |
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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: 4 |
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- total_train_batch_size: 8 |
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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: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.9894 | 0.13 | 1 | 1.5790 | |
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| 1.915 | 0.26 | 2 | 1.4849 | |
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| 1.642 | 0.52 | 4 | 1.4032 | |
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| 1.5396 | 0.77 | 6 | 1.4059 | |
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| 1.3746 | 1.03 | 8 | 1.4101 | |
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| 0.9355 | 1.23 | 10 | 1.5147 | |
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| 0.9266 | 1.48 | 12 | 1.5291 | |
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| 0.8006 | 1.74 | 14 | 1.4724 | |
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| 0.7664 | 2.0 | 16 | 1.4965 | |
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| 0.4813 | 2.16 | 18 | 1.5715 | |
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| 0.4193 | 2.42 | 20 | 1.5436 | |
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| 0.364 | 2.68 | 22 | 1.6040 | |
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| 0.3592 | 2.94 | 24 | 1.5823 | |
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| 0.1884 | 3.13 | 26 | 1.6850 | |
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| 0.159 | 3.39 | 28 | 1.8316 | |
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| 0.1641 | 3.65 | 30 | 1.7286 | |
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| 0.1512 | 3.9 | 32 | 1.7029 | |
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| 0.1563 | 4.06 | 34 | 1.7033 | |
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| 0.0696 | 4.32 | 36 | 1.7482 | |
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| 0.0643 | 4.58 | 38 | 1.8069 | |
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| 0.0662 | 4.84 | 40 | 1.8410 | |
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| 0.0709 | 5.1 | 42 | 1.8529 | |
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| 0.0344 | 5.26 | 44 | 1.8626 | |
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| 0.0468 | 5.52 | 46 | 1.8716 | |
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| 0.0328 | 5.77 | 48 | 1.8761 | |
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| 0.0353 | 6.03 | 50 | 1.8789 | |
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| 0.0375 | 6.23 | 52 | 1.8803 | |
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| 0.0345 | 6.48 | 54 | 1.8802 | |
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| 0.0346 | 6.74 | 56 | 1.8806 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.0.1 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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