/content/eu_ai_model_mistral7b
Browse files- README.md +96 -0
- adapter_config.json +29 -0
- adapter_model.safetensors +3 -0
- runs/Sep27_14-06-12_e43ae22af8f2/events.out.tfevents.1727445979.e43ae22af8f2.1867.0 +3 -0
- runs/Sep27_14-12-04_e43ae22af8f2/events.out.tfevents.1727446396.e43ae22af8f2.1867.1 +3 -0
- runs/Sep27_14-14-46_e43ae22af8f2/events.out.tfevents.1727446490.e43ae22af8f2.8258.0 +3 -0
- runs/Sep27_14-40-16_e43ae22af8f2/events.out.tfevents.1727448033.e43ae22af8f2.14823.0 +3 -0
- runs/Sep27_14-40-50_e43ae22af8f2/events.out.tfevents.1727448054.e43ae22af8f2.14823.1 +3 -0
- runs/Sep27_14-41-57_e43ae22af8f2/events.out.tfevents.1727448121.e43ae22af8f2.15440.0 +3 -0
- training_args.bin +3 -0
README.md
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---
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base_model: mistralai/Mistral-7B-v0.1
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library_name: peft
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license: apache-2.0
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tags:
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- generated_from_trainer
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model-index:
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- name: results
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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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# results
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.4476
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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: 0.001
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- train_batch_size: 2
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 4
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 17
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- training_steps: 1792
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 2.8156 | 0.1115 | 50 | 1.7682 |
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| 1.6754 | 0.2230 | 100 | 1.6347 |
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| 1.5257 | 0.3344 | 150 | 1.5543 |
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| 1.5435 | 0.4459 | 200 | 1.5301 |
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| 1.613 | 0.5574 | 250 | 1.5579 |
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| 1.6178 | 0.6689 | 300 | 1.6006 |
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| 1.675 | 0.7804 | 350 | 1.5209 |
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| 1.5046 | 0.8919 | 400 | 1.5203 |
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| 1.5977 | 1.0033 | 450 | 1.5253 |
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| 1.5303 | 1.1148 | 500 | 1.4984 |
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| 1.4748 | 1.2263 | 550 | 1.5073 |
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| 1.4955 | 1.3378 | 600 | 1.4998 |
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| 1.5737 | 1.4493 | 650 | 1.5405 |
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| 1.5662 | 1.5608 | 700 | 1.5147 |
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| 1.417 | 1.6722 | 750 | 1.5047 |
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| 1.5732 | 1.7837 | 800 | 1.4768 |
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| 1.5077 | 1.8952 | 850 | 1.4948 |
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| 1.5634 | 2.0067 | 900 | 1.4768 |
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| 1.5219 | 2.1182 | 950 | 1.4752 |
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| 1.4073 | 2.2297 | 1000 | 1.4776 |
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| 1.4915 | 2.3411 | 1050 | 1.4799 |
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| 1.4585 | 2.4526 | 1100 | 1.4868 |
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| 1.4979 | 2.5641 | 1150 | 1.4703 |
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| 1.4755 | 2.6756 | 1200 | 1.4617 |
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| 1.4167 | 2.7871 | 1250 | 1.4576 |
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| 1.5095 | 2.8986 | 1300 | 1.4651 |
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| 1.477 | 3.0100 | 1350 | 1.4526 |
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| 1.4495 | 3.1215 | 1400 | 1.4660 |
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| 1.5609 | 3.2330 | 1450 | 1.4547 |
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| 1.4319 | 3.3445 | 1500 | 1.4478 |
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| 1.3469 | 3.4560 | 1550 | 1.4597 |
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| 1.4454 | 3.5674 | 1600 | 1.4478 |
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| 1.4071 | 3.6789 | 1650 | 1.4506 |
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| 1.3686 | 3.7904 | 1700 | 1.4485 |
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| 1.4958 | 3.9019 | 1750 | 1.4476 |
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### Framework versions
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- PEFT 0.13.0
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- Transformers 4.44.2
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- Pytorch 2.4.1+cu121
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- Datasets 3.0.1
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- Tokenizers 0.19.1
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "mistralai/Mistral-7B-v0.1",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 8,
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"lora_dropout": 0.1,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 8,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"q_proj",
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"v_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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training_args.bin
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