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--- |
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base_model: mistralai/Mistral-7B-Instruct-v0.3 |
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datasets: |
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- generator |
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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_7b_cosine_lr |
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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_7b_cosine_lr |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3803 |
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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: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_ratio: 0.03 |
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- lr_scheduler_warmup_steps: 15 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.0242 | 0.0366 | 10 | 0.6227 | |
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| 0.5884 | 0.0732 | 20 | 0.5310 | |
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| 0.519 | 0.1098 | 30 | 0.4930 | |
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| 0.4818 | 0.1465 | 40 | 0.4653 | |
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| 0.4722 | 0.1831 | 50 | 0.4537 | |
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| 0.4513 | 0.2197 | 60 | 0.4440 | |
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| 0.4481 | 0.2563 | 70 | 0.4377 | |
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| 0.4455 | 0.2929 | 80 | 0.4321 | |
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| 0.4344 | 0.3295 | 90 | 0.4271 | |
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| 0.4345 | 0.3661 | 100 | 0.4233 | |
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| 0.4296 | 0.4027 | 110 | 0.4186 | |
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| 0.4255 | 0.4394 | 120 | 0.4166 | |
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| 0.4173 | 0.4760 | 130 | 0.4131 | |
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| 0.4195 | 0.5126 | 140 | 0.4098 | |
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| 0.4143 | 0.5492 | 150 | 0.4067 | |
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| 0.4103 | 0.5858 | 160 | 0.4043 | |
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| 0.4124 | 0.6224 | 170 | 0.4021 | |
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| 0.4069 | 0.6590 | 180 | 0.3988 | |
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| 0.4041 | 0.6957 | 190 | 0.3981 | |
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| 0.4044 | 0.7323 | 200 | 0.3951 | |
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| 0.3989 | 0.7689 | 210 | 0.3912 | |
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| 0.3947 | 0.8055 | 220 | 0.3895 | |
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| 0.3945 | 0.8421 | 230 | 0.3868 | |
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| 0.3876 | 0.8787 | 240 | 0.3849 | |
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| 0.3877 | 0.9153 | 250 | 0.3839 | |
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| 0.3922 | 0.9519 | 260 | 0.3817 | |
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| 0.3844 | 0.9886 | 270 | 0.3796 | |
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| 0.3491 | 1.0252 | 280 | 0.3832 | |
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| 0.3291 | 1.0618 | 290 | 0.3821 | |
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| 0.3267 | 1.0984 | 300 | 0.3803 | |
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### Framework versions |
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- PEFT 0.13.2 |
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- Transformers 4.45.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
