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--- |
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library_name: transformers |
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license: cc-by-nc-4.0 |
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base_model: Salesforce/xgen-small-4B-instruct-r |
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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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- hardlyworking/HardlyRPv2 |
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model-index: |
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- name: HoldMy4B |
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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: `0.10.0` |
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```yaml |
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base_model: Salesforce/xgen-small-4B-instruct-r |
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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: hardlyworking/HardlyRPv2 |
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type: chat_template |
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split: train |
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field_messages: conversations |
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message_property_mappings: |
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role: from |
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content: value |
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val_set_size: 0.1 |
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output_dir: ./outputs/out |
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dataset_prepared_path: last_run_prepared |
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shuffle_merged_datasets: true |
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hub_model_id: hardlyworking/HoldMy4B |
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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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plugins: |
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- axolotl.integrations.liger.LigerPlugin |
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- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin |
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liger_rope: true |
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liger_rms_norm: true |
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liger_layer_norm: true |
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liger_glu_activation: true |
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liger_fused_linear_cross_entropy: false |
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cut_cross_entropy: true |
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sequence_len: 32768 |
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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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wandb_project: Xgen4B |
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wandb_entity: |
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wandb_watch: |
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wandb_name: Xgen4B |
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wandb_log_model: |
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evals_per_epoch: 8 |
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eval_table_size: |
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eval_max_new_tokens: 128 |
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gradient_accumulation_steps: 2 |
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micro_batch_size: 2 |
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num_epochs: 2 |
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optimizer: adamw_bnb_8bit |
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lr_scheduler: cosine |
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learning_rate: 1e-5 |
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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: offload |
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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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xformers_attention: |
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flash_attention: true |
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s2_attention: |
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deepspeed: |
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warmup_ratio: 0.05 |
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saves_per_epoch: 1 |
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debug: |
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weight_decay: 0.01 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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pad_token: |
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``` |
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</details><br> |
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# HoldMy4B |
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This model is a fine-tuned version of [Salesforce/xgen-small-4B-instruct-r](https://huggingface.co/Salesforce/xgen-small-4B-instruct-r) on the hardlyworking/HardlyRPv2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1637 |
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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: 1e-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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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- total_eval_batch_size: 4 |
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- optimizer: Use OptimizerNames.ADAMW_BNB 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: 24 |
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- training_steps: 480 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| No log | 0 | 0 | 2.6420 | |
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| 2.0119 | 0.125 | 30 | 2.2105 | |
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| 1.8963 | 0.25 | 60 | 2.1865 | |
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| 1.8623 | 0.375 | 90 | 2.1787 | |
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| 1.8528 | 0.5 | 120 | 2.1746 | |
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| 1.8784 | 0.625 | 150 | 2.1706 | |
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| 1.9961 | 0.75 | 180 | 2.1686 | |
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| 1.8748 | 0.875 | 210 | 2.1672 | |
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| 2.0385 | 1.0 | 240 | 2.1657 | |
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| 1.9327 | 1.125 | 270 | 2.1646 | |
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| 1.8509 | 1.25 | 300 | 2.1645 | |
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| 1.8279 | 1.375 | 330 | 2.1640 | |
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| 1.8271 | 1.5 | 360 | 2.1638 | |
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| 1.8589 | 1.625 | 390 | 2.1637 | |
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| 1.9824 | 1.75 | 420 | 2.1637 | |
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| 1.8668 | 1.875 | 450 | 2.1637 | |
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| 2.0332 | 2.0 | 480 | 2.1637 | |
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### Framework versions |
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- Transformers 4.52.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
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