LLM-Alchemy-Chamber/mistral-instruct-generation
Browse files- README.md +18 -18
- adapter_config.json +3 -3
- adapter_model.safetensors +1 -1
- runs/Aug02_10-11-21_genertive-ai-workbench-0/events.out.tfevents.1722593484.genertive-ai-workbench-0.3881.0 +3 -0
- runs/Aug02_15-08-44_genertive-ai-workbench-0/events.out.tfevents.1722611325.genertive-ai-workbench-0.348.0 +3 -0
- runs/Aug03_05-27-29_genertive-ai-workbench-0/events.out.tfevents.1722662851.genertive-ai-workbench-0.302.0 +3 -0
- runs/Aug03_05-48-06_genertive-ai-workbench-0/events.out.tfevents.1722664088.genertive-ai-workbench-0.828.0 +3 -0
- runs/Aug03_06-43-15_genertive-ai-workbench-0/events.out.tfevents.1722667396.genertive-ai-workbench-0.1335.0 +3 -0
- runs/Aug03_07-07-56_genertive-ai-workbench-0/events.out.tfevents.1722668878.genertive-ai-workbench-0.1753.0 +3 -0
- training_args.bin +2 -2
README.md
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---
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library_name: peft
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tags:
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- generated_from_trainer
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base_model: mistralai/Mixtral-8x7B-v0.1
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model-index:
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- name: Mixtral_Alpace_v3
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results: []
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This model is a fine-tuned version of [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 2.5e-05
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- train_batch_size:
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- eval_batch_size: 8
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- seed: 42
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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:
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- training_steps: 100
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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### Framework versions
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- PEFT 0.
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- Transformers 4.36.0
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- Pytorch 2.
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- Datasets 2.
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- Tokenizers 0.15.2
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---
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base_model: mistralai/Mixtral-8x7B-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: Mixtral_Alpace_v3
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results: []
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This model is a fine-tuned version of [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8517
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 2.5e-05
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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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: 3
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- training_steps: 100
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 1.1536 | 0.03 | 10 | 1.1278 |
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| 1.0733 | 0.07 | 20 | 1.0587 |
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| 1.0201 | 0.1 | 30 | 0.9941 |
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| 0.9622 | 0.13 | 40 | 0.9509 |
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| 0.9268 | 0.16 | 50 | 0.9188 |
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| 0.8984 | 0.2 | 60 | 0.8944 |
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| 0.9067 | 0.23 | 70 | 0.8756 |
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| 0.8712 | 0.26 | 80 | 0.8622 |
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| 0.8485 | 0.3 | 90 | 0.8544 |
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| 0.8703 | 0.33 | 100 | 0.8517 |
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### Framework versions
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- PEFT 0.12.1.dev0
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- Transformers 4.36.0
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- Pytorch 2.2.2+cu121
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- Datasets 2.20.0
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- Tokenizers 0.15.2
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adapter_config.json
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"k_proj",
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"up_proj",
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"o_proj",
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"down_proj",
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"lm_head",
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"v_proj",
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"gate_proj"
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],
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"task_type": "CAUSAL_LM",
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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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"lm_head",
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"k_proj",
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"up_proj",
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"v_proj",
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"o_proj",
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"down_proj",
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"gate_proj"
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"task_type": "CAUSAL_LM",
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adapter_model.safetensors
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training_args.bin
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