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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: mistralai/Mistral-Nemo-Instruct-2407
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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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- linabot/train_data
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model-index:
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- name: linabot
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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: `0.8.0`
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```yaml
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base_model: mistralai/Mistral-Nemo-Instruct-2407
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model_type: MistralForCausalLM
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hub_model_id: Alignment-Lab-AI/linabot
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strict: false
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chat_template: tokenizer_default
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plugins:
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- axolotl.integrations.liger.LigerPlugin
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liger_rope: true
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liger_rms_norm: true
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liger_glu_activation: true
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liger_layer_norm: true
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liger_fused_linear_cross_entropy: true
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datasets:
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- path: linabot/train_data
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type: chat_template
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field_messages: messages
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message_property_mappings:
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role: role
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content: content
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roles_to_train: ['assistant', 'user']
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train_on_eos: turn
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learning_rate: 2e-5
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lr_scheduler: cosine
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weight_decay: 0.03
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warmup_steps: 450
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dataset_prepared_path:
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val_set_size: 0.2
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output_dir: ./outputs/out
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sequence_len: 10400
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sample_packing: true
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pad_to_sequence_len: true
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eval_sample_packing: true
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wandb_project: linabot
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wandb_entity:
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wandb_watch: all
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wandb_name:
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wandb_log_model:
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gradient_accumulation_steps: 1
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micro_batch_size: 4
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num_epochs: 5
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optimizer: adalomo
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lr_scheduler: cosine
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learning_rate: 0.0002024
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flash_attention: true
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flash_attn_cross_entropy: false
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flash_attn_rms_norm: true
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flash_attn_fuse_qkv: false
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flash_attn_fuse_mlp: true
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torch_compile_mode: "max-autotune"
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bf16: auto
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tf32: false
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gradient_checkpointing: true
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resume_from_checkpoint:
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logging_steps: 1
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evals_per_epoch: 8
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saves_per_epoch: 1
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weight_decay: 0.03
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special_tokens:
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bos_token: "<s>"
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eos_token: "</s>"
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pad_token: "<pad>"
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```
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</details><br>
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# linabot
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This model is a fine-tuned version of [mistralai/Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407) on the linabot/train_data dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0558
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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: 0.0002024
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- optimizer: Use OptimizerNames.ADALOMO and the args are:
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No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 450
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- num_epochs: 5.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 1.526 | 0.0083 | 1 | 1.5474 |
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| 1.5934 | 0.125 | 15 | 1.5472 |
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| 1.5242 | 0.25 | 30 | 1.5454 |
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| 1.5296 | 0.375 | 45 | 1.5408 |
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| 1.5087 | 0.5 | 60 | 1.5322 |
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| 1.486 | 0.625 | 75 | 1.5188 |
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| 1.4314 | 0.75 | 90 | 1.5005 |
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| 1.4311 | 0.875 | 105 | 1.4782 |
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| 1.4532 | 1.0 | 120 | 1.4513 |
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| 1.4215 | 1.125 | 135 | 1.4198 |
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| 1.3248 | 1.25 | 150 | 1.3825 |
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| 1.2697 | 1.375 | 165 | 1.3386 |
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| 1.3281 | 1.5 | 180 | 1.2880 |
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| 1.2428 | 1.625 | 195 | 1.2296 |
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| 1.1533 | 1.75 | 210 | 1.1596 |
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| 1.1038 | 1.875 | 225 | 1.0747 |
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| 1.0226 | 2.0 | 240 | 0.9723 |
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| 0.8858 | 2.125 | 255 | 0.8467 |
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| 0.6762 | 2.25 | 270 | 0.7047 |
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| 0.6433 | 2.375 | 285 | 0.5626 |
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| 0.4017 | 2.5 | 300 | 0.4283 |
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| 0.2875 | 2.625 | 315 | 0.3072 |
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| 0.2244 | 2.75 | 330 | 0.2161 |
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| 0.1445 | 2.875 | 345 | 0.1572 |
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| 0.0898 | 3.0 | 360 | 0.1192 |
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| 0.0666 | 3.125 | 375 | 0.0991 |
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| 0.0605 | 3.25 | 390 | 0.0855 |
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| 0.0457 | 3.375 | 405 | 0.0757 |
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| 0.052 | 3.5 | 420 | 0.0700 |
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| 0.0634 | 3.625 | 435 | 0.0658 |
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| 0.0364 | 3.75 | 450 | 0.0623 |
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| 0.045 | 3.875 | 465 | 0.0601 |
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| 0.0395 | 4.0 | 480 | 0.0582 |
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| 0.0558 | 4.125 | 495 | 0.0573 |
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| 0.0468 | 4.25 | 510 | 0.0566 |
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| 0.0399 | 4.375 | 525 | 0.0562 |
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| 0.0337 | 4.5 | 540 | 0.0560 |
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| 0.0413 | 4.625 | 555 | 0.0559 |
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| 0.0318 | 4.75 | 570 | 0.0558 |
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| 0.0435 | 4.875 | 585 | 0.0558 |
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| 0.0445 | 5.0 | 600 | 0.0558 |
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### Framework versions
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- Transformers 4.51.1
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- Pytorch 2.6.0+cu124
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- Datasets 3.5.0
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- Tokenizers 0.21.1
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