Model save
Browse files- README.md +70 -0
- all_results.json +9 -0
- train_results.json +9 -0
- trainer_state.json +109 -0
README.md
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---
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base_model: mistralai/Mistral-7B-Instruct-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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- trl
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- sft
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- generated_from_trainer
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model-index:
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- name: mistral_alpaca_llama_2_lora
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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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# mistral_alpaca_llama_2_lora
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9171
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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: 0.0002
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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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- 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: 16
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- total_eval_batch_size: 8
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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_ratio: 0.1
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- training_steps: 20
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 1.6561 | 0.7692 | 5 | 1.3224 |
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| 0.9841 | 1.5385 | 10 | 1.0236 |
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| 0.8154 | 2.3077 | 15 | 0.9388 |
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| 0.7534 | 3.0769 | 20 | 0.9171 |
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### Framework versions
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- PEFT 0.12.0
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- Transformers 4.44.2
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- Pytorch 2.4.1+cu121
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- Datasets 3.0.0
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- Tokenizers 0.19.1
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all_results.json
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"train_samples_per_second": 3.752,
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"train_steps_per_second": 0.234
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}
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train_results.json
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"train_steps_per_second": 0.234
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}
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trainer_state.json
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