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--- |
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license: apache-2.0 |
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base_model: scb10x/typhoon-7b |
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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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<!-- 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: scb10x/typhoon-7b |
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model_type: MistralForCausalLM |
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tokenizer_type: LlamaTokenizer |
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is_mistral_derived_model: true |
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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: finetune-data.jsonl |
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type: alpaca |
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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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sequence_len: 8192 |
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sample_packing: false |
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pad_to_sequence_len: true |
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eval_sample_packing: false |
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wandb_project: typhoon-7b |
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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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gradient_accumulation_steps: 8 |
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micro_batch_size: 1 |
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num_epochs: 4 |
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optimizer: adamw_bnb_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.000005 |
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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 |
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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_ratio: 0.05 |
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evals_per_epoch: 5 |
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eval_table_size: |
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eval_table_max_new_tokens: 128 |
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saves_per_epoch: 5 |
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save_total_limit: 10 |
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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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bos_token: "<s>" |
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eos_token: "</s>" |
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unk_token: "<unk>" |
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``` |
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</details><br> |
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# out |
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This model is a fine-tuned version of [scb10x/typhoon-7b](https://huggingface.co/scb10x/typhoon-7b) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7682 |
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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: 1 |
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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: 2 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 16 |
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- total_eval_batch_size: 2 |
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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: 23 |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 3.4821 | 0.0 | 1 | 4.2554 | |
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| 0.7752 | 0.2 | 48 | 0.7134 | |
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| 0.7287 | 0.41 | 96 | 0.6403 | |
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| 0.6135 | 0.61 | 144 | 0.6305 | |
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| 0.7828 | 0.81 | 192 | 0.6020 | |
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| 0.3375 | 1.02 | 240 | 0.5951 | |
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| 0.471 | 1.22 | 288 | 0.6191 | |
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| 0.2798 | 1.42 | 336 | 0.6249 | |
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| 0.5071 | 1.63 | 384 | 0.6213 | |
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| 0.2792 | 1.83 | 432 | 0.6176 | |
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| 0.069 | 2.03 | 480 | 0.6393 | |
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| 0.0742 | 2.23 | 528 | 0.6877 | |
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| 0.1309 | 2.44 | 576 | 0.6892 | |
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| 0.0349 | 2.64 | 624 | 0.6701 | |
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| 0.0639 | 2.84 | 672 | 0.6657 | |
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| 0.0273 | 3.05 | 720 | 0.6895 | |
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| 0.0311 | 3.25 | 768 | 0.7606 | |
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| 0.0307 | 3.45 | 816 | 0.7636 | |
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| 0.0791 | 3.66 | 864 | 0.7664 | |
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| 0.0747 | 3.86 | 912 | 0.7682 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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