Model save
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README.md
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---
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license: apache-2.0
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library_name: peft
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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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base_model: mistralai/Mistral-7B-v0.1
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datasets:
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- generator
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model-index:
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- name: zephyr-7b-sft-qlora
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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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# zephyr-7b-sft-qlora
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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 generator dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9499
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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: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 4
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 32
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- total_eval_batch_size: 32
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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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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 0.9462 | 1.0 | 4357 | 0.9499 |
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### Framework versions
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- PEFT 0.7.1
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- Transformers 4.38.2
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- Pytorch 2.1.2
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- Datasets 2.14.6
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- Tokenizers 0.15.2
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adapter_model.safetensors
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size 83946192
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all_results.json
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{
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"epoch": 1.0,
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"train_loss": 0.9569843266025059,
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"train_runtime": 33545.7523,
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"train_samples": 207865,
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"train_samples_per_second": 4.156,
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"train_steps_per_second": 0.13
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}
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runs/Mar06_16-31-59_ale-llm-4-0-0/events.out.tfevents.1709742750.ale-llm-4-0-0.1626.0
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size 189625
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train_results.json
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{
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"epoch": 1.0,
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"train_loss": 0.9569843266025059,
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"train_runtime": 33545.7523,
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"train_samples": 207865,
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"train_samples_per_second": 4.156,
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"train_steps_per_second": 0.13
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}
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trainer_state.json
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